




Fast signal transforms with lifting steps 
RE40081 
Fast signal transforms with lifting steps


Patent Drawings: 
(5 images) 

Inventor: 
Tran, et al. 
Date Issued: 
February 19, 2008 
Application: 
10/629,303 
Filed: 
July 29, 2003 
Inventors: 
Tran; Trac D. (Columbia, MD) Topiwala; Pankaj (Clarksville, MD)

Assignee: 
Fast VDO LLC (Columbia, MD) 
Primary Examiner: 
Couso; Jose L. 
Assistant Examiner: 

Attorney Or Agent: 
Burns & Levinson LLPWhitehead; Kimberly B. 
U.S. Class: 
382/232 
Field Of Search: 
382/232; 382/233; 382/236; 382/238; 382/239; 382/240; 382/242; 382/248; 382/250; 358/426.13; 358/426.14; 348/384.1; 348/394.1; 348/395.1; 348/400.1; 348/401.1; 348/402.1; 348/403.1; 348/404.1; 348/407.1; 348/408.1; 348/409.1; 348/410.1; 348/411.1; 348/412.1; 348/413.1; 348/414.1; 348/415.1; 348/416.1; 348/420.1; 348/421.1; 348/425.1; 348/430.1; 348/431.1; 348/699; 341/51; 341/63; 341/65; 341/67; 341/107; 364/724.011; 364/724.04; 364/724.05; 364/724.13; 364/724.14; 364/725.01; 364/725.02; 708/400; 375/240.11; 375/240.16 
International Class: 
G06K 9/36 
U.S Patent Documents: 

Foreign Patent Documents: 

Other References: 
Liang et al., "ITUTelecommunications Standardization Sector", A 16bit architecture for H.26L treating DCT Transforms and quantization, pp.112, May 29, 2001. cited by examiner. Sweldens, Wim, "The Lifting Scheme: A custom design construction of biorthogonal wavelets", pp. 129, Nov. 1994. cited by examiner. Nayebi et al., "A time domain view of filter banks and wavelets", Signals, Systems and Computers, 1991. 1991 Conference Record of the TwentyFifth Asimolar Conference on, 1991, pp. 736740 vol. 2. cited by examiner. Liang, et al., "ITUTelecommunications Standardization Sector", A 16bit architecture for H.26L treating DCT Transforms anf quantization, pp. 12, May 29, 2001. cited by examiner. 

Abstract: 
This invention introduces a class of multiband linear phase lapped biorthogonal transforms with fast, VLSIfriendly implementations via lifting steps called the LiftLT. The transform is based on a lattice structure which robustly enforces both linear phase and perfect reconstruction properties. The lattice coefficients are parameterized as a series of lifting steps, providing fast, efficient inplace computation of the transform coefficients as well as the ability to map integers to integers. Our main motivation of the new transform is its application in image and video coding. Comparing to the popular 8.times.8 DCT, the 8.times.16 LiftLT only requires 1 more multiplication, 22 more additions, and 6 more shifting operations. However, image coding examples show that the LiftLT is far superior to the DCT in both objective and subjective coding performance. Thanks to properly designed overlapping basis functions, the LiftLT can completely eliminate annoying blocking artifacts. In fact, the novel LiftLT's coding performance consistently surpasses that of the much more complex 9/7tap biorthogonal wavelet with floatingpoint coefficients. More importantly, our transform's blockbased nature facilitates onepass sequential block coding, regionofinterest coding/decoding as well as parallel processing. 
Claim: 
We claim:
1. An apparatus for coding, storing or transmitting, and decoding M.times.M sized blocks of digitally represented images, where M is an even number.Iadd., .Iaddend.comprising a. aforward transform comprising i. a base transform having M channels numbered 0 through M1, half of said channel numbers being odd and half being even; ii. an equal normalization factor in each of the M channels selected to be dyadicrational; iii. afullscale butterfly implemented as a series of lifting steps with a first set of dyadic rational coefficients; iv. M/2 delay lines in the odd numbered channels; v. a fullscale butterfly implemented as a series of lifting steps with said first set ofdyadic rational coefficients; and vi. a series of lifting steps in the odd numbered channels with a second specifically selected set of dyadicrational coefficients; b. means for transmission or storage of the transform output coefficients; and c. aninverse transform comprising i. M channels numbered 0 through M1, half of said channel numbers being odd and half being even; ii. a series of inverse lifting steps in the odd numbered channels with said second set of specifically selecteddyadicrational coefficients; iii. a fullscale butterfly implemented as a series of lifting steps with said first set of specifically selected dyadicrational coefficients; iv. M/2 delay lines in the even numbered channels; v. a fullscalebutterfly implemented as a series of lifting steps with said first set of specifically selected dyadicrational coefficients; vi. an equal denormalization factor in each of the M channels specifically selected to be dyadicrational; and vii. a baseinverse transform having M channels numbered 0 through M1.
2. The apparatus of claim 1 in which the normalizing factor takes the value 25/16 and simultaneously the denormalizing factor takes the value 16/25.
3. The apparatus of claim 1 in which the normalizing factor takes the value 5/4 and simultaneously the denormalizing factor takes the value 4/5.
4. The apparatus of claim 1 in which the first set of dyadic rational coefficients are all equal to 1.
5. The apparatus of claim 1 in which the second set of dyadic rational coefficients are all equal to 1/2.
6. The apparatus of claim 1 in which the base transform is any M.times.M invertible matrix of the form of a linear phase filter and the inverse base transform is the inverse of said M.times.M invertible matrix.
7. The apparatus of claim 1 in which the base transform is the forward M.times.M discrete cosine transform and the inverse base transform is the inverse M.times.M discrete cosine transform.
8. An apparatus for coding, compressing, storing or transmitting, and decoding a block of M.times.M intensities from a digital image selected by an M.times.M window moving recursively over the image, comprising: a. an M.times.M block transformcomprising: i. an initial stage ii. a normalizing factor in each channel b. a cascade comprising a plurality of dyadic rational lifting transforms, each of said plurality of dyadic rational lifting transforms comprising i. a first bank of pairs ofbutterfly lifting steps with unitary coefficients between adjacent lines of said transform; ii. a bank of delay lines in a first group of M/2 alternating lines; iii. a second bank of butterfly lifting steps with unitary coefficients, and iv. a bankof pairs of butterfly lifting steps with coefficients of 1/2 between M/21 pairs of said M/2 alternating lines; c. means for transmission or storage of the output coefficients of said M.times.M block transform; and d. an inverse transform comprising i.a cascade comprising a plurality of dyadic rational lifting transforms, each of said plurality of dyadic rational lifting transforms comprising a) a bank of pairs of butterfly lifting steps with coefficients of 1/2 between said M/21 pairs of said M/2alternating lines; b) a first bank of pairs of butterfly lifting steps with unitary coefficients between adjacent lines of said transform; c) a bank of delay lines in a second group of M/2 alternating lines.[.,.]. .Iadd.; .Iaddend.and d) a secondbank of pairs of butterfly lifting steps with unitary coefficients between adjacent lines of said transform; ii. a descaling bank.[.,.]. .Iadd.; .Iaddend.and iii. an inverse initial stage.
9. A method of coding, storing or transmitting, and decoding M.times.M sized blocks of digitally represented images, where M is .[.an even number.]. .Iadd.a power of 2.Iaddend., comprising a. transmitting the original picture signals to acoder, which effects the steps of i. converting the signals with a base transform having M channels numbered 0 through M1, half of said channel numbers being odd and half being even.[.,.]. .Iadd.;.Iaddend. ii. normalizing the output of the precedingstep with a dyadic rational normalization factor in each of said M channels; iii. processing the output of the preceding step through two lifting steps with a first set of identical dyadic rational coefficients connecting each pair of adjacent numberedchannels in a butterfly configuration; iv. transmitting the resulting coefficients through M/2 delay lines in the odd numbered channels; v. processing the output of the preceding step through two inverse lifting steps with the first set of dyadicrational coefficients connecting each pair of adjacent numbered channels in a butterfly configuration; and vi. applying two lifting steps with a second set of identical dyadic rational coefficients connecting each pair of adjacent odd numbered channelsto the output of the preceding step; b. transmitting or storing the transform output coefficients; c. receiving the transform output coefficients in a decoder; and d. processing the output coefficients in a decoder, comprising the steps of i.receiving the coefficients in M channels numbered 0 through M1, half of said channel numbers being odd and half being even; ii. applying two inverse lifting steps with dyadic rational coefficients connecting each pair of adjacent odd numberedchannels; iii. applying two lifting steps with dyadic rational coefficients connecting each pair of adjacent numbered channels in a butterfly configuration; iv. transmitting the result of the preceding step through M/2 delay lines in the evennumbered channels; v. applying two inverse lifting steps with dyadic rational coefficients connecting each pair of adjacent numbered channels in a butterfly configuration; vi. denormalizing the result of the preceding step with a dyadic rationalinverse normalization factor in each of said M channels; and vii. processing the result of the preceding step through a base inverse transform having M channels numbered 0 through M1.
10. A method of coding, compressing, storing or transmitting, and decoding a block of M.times.M intensities from a digital image selected by an M.times.M window moving recursively over the image, comprising the steps of: a. Processing theintensities in an M.times.M block coder comprising the steps of: i. processing the intensities through an initial stage; ii. scaling the result of the preceding step in each channel; b. processing the result of the preceding step through a cascadecomprising a plurality of dyadic rational lifting transforms, each of said plurality of dyadic rational lifting transforms comprising i. a first bank of pairs of butterfly lifting steps with unitary coefficients between adjacent lines of said transform; ii. a bank of delay lines in a first group of M/2 alternating lines; iii. a second bank of butterfly lifting steps with unitary coefficients, and iv. a bank of pairs of butterfly lifting steps with coefficients of 1/2 between M/21 pairs of said M/2alternating lines; c. transmitting or storing the output coefficients of said M.times.M block coder; d. receiving the output coefficients in a decoder; and e. processing the output coefficients in the decoder, comprising the steps of i. processing theoutput coefficients through a cascade comprising a plurality of dyadic rational lifting transforms, each of said plurality of dyadic rational lifting transforms comprising a) a bank of pairs of butterfly lifting steps with coefficients of 1/2 betweensaid M/21 pairs of said M/2 alternating lines; b) a first bank of pairs of butterfly lifting steps with unitary coefficients between adjacent lines of said transform; c) a bank of delay lines in a second group of M/2 alternating lines; d) a secondbank of pairs of butterfly lifting steps with unitary coefficients between adjacent lines of said transform; e) a descaling bank; and f. processing the results of the preceding step in an inverse initial stage.
11. The apparatus of claim 1 in which the .[.constants.]. .Iadd.coefficients .Iaddend.are approximations chosen for rapid computing rather than exact .[.constants.]. .Iadd.coefficients.Iaddend..
.Iadd.12. A method of coding, storing or transmitting, and decoding a block of M.times.M intensities from a digital image selected by an M.times.M window moving recursively over the image, comprising: a. processing the intensities in anM.times.M block coder comprising the steps of: i. processing the intensities through an initial stage; ii. scaling the result of the preceding step in each channel; b. processing the result of the preceding step through a transform coder using amethod of processing blocks of samples of digital signals of integer length M comprising processing the digital samples of length M with an invertible linear transform of dimension M, said transform being representable as a cascade, using the steps, inarbitrary order, of: i) at least one +/1 butterfly step, ii) at least one lifting step with rational complex coefficients, and iii) at least one scaling factor; c. transmitting or storing the output coefficients of said M.times.M block coder; d.receiving the output coefficients in a decoder; and e. processing the output coefficients in the decoder into a reconstructed image using the inverse of the coder of steps a. and b..Iaddend.
.Iadd.13. The method of claim 12 wherein the method of processing blocks of samples of digital signals of integer length M additionally comprises the step of at least one time delay..Iaddend.
.Iadd.14. The method of claim 12, wherein the rational complex coefficients in the at least one lifting step are dyadic..Iaddend.
.Iadd.15. The method of claim 12, wherein a) said invertible transform is an approximation of a biorthogonal transform; b) said biorthogonal transformation comprises a representation as a cascade of at least one butterfly step, at least oneorthogonal transform, and at least one scaling factor; c) said at least one orthogonal transform comprises a cascade of i) at least one .+.1 butterfly step, ii) at least one planar rotation, and iii) at least one scaling factor; b) said at least oneplanar rotation being represented by equivalent lifting steps and scale factors; and, c) said approximation is obtained by replacing floating point coefficients in the lifting steps with rational coefficients..Iaddend.
.Iadd.16. The method of claim 15, wherein the coefficients of the lifting steps are chosen to be dyadic rational..Iaddend.
.Iadd.17. The method of claim 12, wherein the invertible transform is a unitary transform..Iaddend.
.Iadd.18. The method of claim 12, wherein a) said invertible transform is an approximation of a unitary transform; b) said approximation of the unitary transform comprises a representation of the unitary transform as a cascade of at least onebutterfly step, at least one orthogonal transform, and at least one scale factor; c) said at least one orthogonal transform being represented as a cascade of (1) at least one .+.1 butterfly steps, (2) at least one planar rotation, and (3) at least onescaling factor; d) said at least one planar rotation being represented by equivalent lifting steps and scale factors; and, e) said approximation being derived by using approximate rational values for the coefficients in the lifting steps..Iaddend.
.Iadd.19. The method of claim 18, wherein the invertible transform is an approximation of a transform selected from the group of special unitary transforms: discrete cosine transform (DCT); discrete Fourier transform (DFT); discrete sinetransform (DST)..Iaddend.
.Iadd.20. The method of claim 18, wherein the coefficients of the lifting steps are dyadic rational..Iaddend.
.Iadd.21. The method of claim 18, wherein at least one of the following lifting steps is used, whose matrix representations take on the form: ##EQU00006## where a, b are selected from the group: .+.{8, 5, 4, 2, 1, 1/2, 1/4, 3/4, 5/4, 1/8, 3/8,2/5, 5/8, 7/8, 1/16, 3/16, 5/16, 7/16, 9/16, 11/16, 13/16, 15/16, 25/16}..Iaddend.
.Iadd.22. The method of claim 21, wherein the invertible transform is an approximation of a transform selected from the group: discrete cosine transform (DCT); discrete Fourier transform (DFT); discrete sine transform (DST)..Iaddend.
.Iadd.23. The method of claim 22, wherein the approximation of the 4 point DCT is selected from the group of matrices:.Iaddend. ##EQU00007##
.Iadd.24. The method of claim 19 in which the invertible transform is an approximation of a transform selected from the group three point DCT, 4 point DCT, 8 point DCT, and 16 point DCT..Iaddend.
.Iadd.25. The method of claim 19 in which the invertible transform is an approximation of a transform selected from the group 512 point FFT, 1024 point FFT, 2048 point FFT, and 4096 point FFT..Iaddend.
.Iadd.26. A method of coding, storing or transmitting, and decoding sequences of intensities of integer length M recursively selected from a time ordered string of intensities arising from electrical signals, the method comprising the steps ofa) recursively processing the sequences of intensities of integer length M with an invertible forward linear transform of dimension M, said transform being representable as a cascade using the steps, in a preselected arbitrary order, of: ii) at least one.+.1 butterfly step, iii) at least one lifting step with rational complex coefficients, and iv) applying at least one scaling factor; b) compressing the resulting transform coefficients; c) storing or transmitting the compressed transformcoefficients; d) receiving or recovering from storage the transmitted or stored compressed transform coefficients; e) decompressing the received or recovered compressed transform coefficients; and f) recursively processing the decompressed transformcoefficients with the inverse of the forward linear transform of dimension M, said inverse transform being representable as a cascade using the steps, in the exact reverse order of the preselected arbitrary order, of: ii) at least one inverse butterflycorresponding to each of the at least one .+.1 butterfly step; iii) at least one inverse lifting step corresponding to each of the at least one lifting step with rational complex coefficients; and, iv) applying at least on inverse scaling factorcorresponding to the at least one scaling factor..Iaddend.
.Iadd.27. The method of claim 26 wherein the method of processing blocks of samples of digital signals of integer length M additionally comprises the step of at least one time delay..Iaddend.
.Iadd.28. The method of claim 26, wherein the rational complex coefficients in the at least one lifting step are dyadic..Iaddend.
.Iadd.29. The method of claim 26, wherein a) said invertible transform is an approximation of a biorthogonal transform; b) said biorthogonal transformation comprises a representation as a cascade of at least one butterfly step, at least oneorthogonal transform, and at least one scaling factor; c) said at least one orthogonal transform comprising a cascade of i) at least one .+.1 butterfly step, ii) at least one planar rotation, and iii) at least one scaling factor; b) said at least oneplanar rotation being represented by equivalent lifting steps and scale factors; and, c) said approximation being obtained by replacing floating point coefficients in the lifting steps with rational coefficients..Iaddend.
.Iadd.30. The method of claim 29, wherein the coefficients of the lifting steps are chosen to be dyadic rational..Iaddend.
.Iadd.31. The method of claim 26, wherein the invertible transform is a unitary transform..Iaddend.
.Iadd.32. The method of claim 26, wherein a) said invertible transform is an approximation of a unitary transform; b) said approximation of the unitary transform comprises a representation of the unitary transform as a cascade of at least onebutterfly step, at least one orthogonal transform, and at least one scale factor; c) said at least one orthogonal transform being represented as a cascade of (1) at least one .+.1 butterfly steps, (2) at least one planar rotation, and (3) at last onescaling factor; d) said at least one planar rotation being represented by equivalent lifting steps and scale factors; and, e) said approximation being derived by using approximate rational values for the coefficients in the lifting steps..Iaddend.
.Iadd.33. The method of claim 32, wherein the invertible transform is an approximation of a transform selected from the group of special unitary transforms: discrete cosine transform (DCT); discrete Fourier transform (DFT); discrete sinetransform (DST)..Iaddend.
.Iadd.34. The method of claim 32, wherein the coefficients of the lifting steps are dyadic rational..Iaddend.
.Iadd.35. The method of claim 32, wherein at least one of the following lifting steps is used, whose matrix representations take on the form: ##EQU00008## where a, b are selected from the group: .+.{8, 5, 4, 2, 1, 1/2, 1/4, 3/4, 5/4, 1/8, 3/8,2/5, 5/8, 7/8, 1/16, 3/16, 5/16, 7/16, 9/16, 11/16, 13/16, 15/16, 25/16}..Iaddend.
.Iadd.36. The method of claim 35, wherein the invertible transform is an approximation of a transform selected from the group: discrete cosine transform (DCT); discrete Fourier transform (DFT); discrete sine transform (DST)..Iaddend.
.Iadd.37. The method of claim 36, wherein the approximation of the 4 point DCT is selected from the group of matrices:.Iaddend. ##EQU00009##
.Iadd.38. The method of claim 33 in which the invertible transform is an approximation of a transform selected from the group three point DCT, 4 point DCT, 8 point DCT, and 16 point DCT..Iaddend.
.Iadd.39. The method of claim 33 in which the invertible transform is an approximation of a transform selected from the group 512 point FFT, 1024 point FFT, 2048 point FFT, and 4096 point FFT..Iaddend. 
Description: 
FIELD OF THE INVENTION
.Iadd.More than one reissue application has been filed for the reissue of U.S. Pat. No. 6,421,464. The Instant Reissue application Ser. No. 10/629,303 filed Jul. 29, 2003 and U.S. application Ser. No. 11/896,522, filed Sep. 4, 2007 whichis a Continuation of U.S. Reissue application Ser. No. 10/629,303..Iaddend.
The current invention relates to the processing of images such as photographs, drawings, and other two dimensional displays. It further relates to the processing of such images which are captured in digital format or after they have beenconverted to or expressed in digital format. This invention further relates to use of novel coding methods to increase the speed and compression ratio for digital image storage and transmission while avoiding introduction of undesirable artifacts intothe reconstructed images.
BACKGROUND OF THE INVENTION
In general, image processing is the analysis and manipulation of twodimensional representations, which can comprise photographs, drawings, paintings, blueprints, xrays of medical patients, or indeed abstract art or artistic patterns. Theseimages are all twodimensional arrays of information. Until fairly recently, images have comprised almost exclusively analog displays of analog information, for example, conventional photographs and motion pictures. Even the signals encoding televisionpictures, notwithstanding that the vertical scan comprises a finite number of lines, are fundamentally analog in nature.
Beginning in the early 1960's, images began to be captured or converted and stored as twodimensional digital data, and digital image processing followed. At first, images were recorded or transmitted in analog form and then converted to digitalrepresentation for manipulation on a computer. Currently digital capture and transmission are on their way to dominance, in part because of the advent of charge coupled device (CCD) image recording arrays and in part because of the availability ofinexpensive high speed computers to store and manipulate images.
An important task of image processing is the correction or enhancement of a particular image. For example, digital enhancement of images of celestial objects taken by space probes has provided substantial scientific information. However, thecurrent invention relates primarily to compression for transmission or storage of digital images and not to enhancement.
One of the problems with digital images is that a complete single image frame can require up to several megabytes of storage space or transmission bandwidth. That is, one of today's 31/2 inch floppy discs can hold at best a little more than onegrayscale frame and sometimes substantially less than one whole frame. A fullpage color picture, for example, uncompressed, can occupy 30 megabytes of storage space. Storing or transmitting the vast amounts of data which would be required forrealtime uncompressed high resolution digital video is technologically daunting and virtually impossible for many important communication channels, such as the telephone line. The transmission of digital images from space probes can take many hours oreven days if insufficiently compressed images are involved. Accordingly, there has been a decades long effort to develop methods of extracting from images the information essential to an aesthetically pleasing or scientifically useful picture withoutdegrading the image quality too much and especially without introducing unsightly or confusing artifacts into the image.
The basic approach has usually involved some form of coding of picture intensities coupled with quantization. One approach is block coding; another approach, mathematically equivalent with proper phasing, is multiphase filter banks. Frequencybased multiband transforms have long found application in image coding. For instance, the JPEG image compression standard, W. B. Pennebaker and J. L. Mitchell, "JPEG: Still Image Compression Standard," Van Nostrand Reinhold, 1993, employs the 8.times.8discrete cosine transform (DCT) at its transformation stage. At high bit rates, JPEG offers almost lossless reconstructed image quality. However, when more compression is needed, annoying blocking artifacts appear since the DCT bases are short and donot overlap, creating discontinuities at block boundaries.
The wavelet transform, on the other hand, with long, varyinglength, and overlapping bases, has elegantly solved the blocking problem. However, the transform's computational complexity can be significantly higher than that of the DCT. Thiscomplexity gap is partly in terms of the number of arithmetical operations involved, but more importantly, in terms of the memory buffer space required. In particular, some implementations of the wavelet transform require many more operations per outputcoefficient as well as a large buffer.
An interesting alternative to wavelets is the lapped transform, e.g., H. S. Malvar, Signal Processing with Lapped Transforms, Artech House, 1992, where pixels from adjacent blocks are utilized in the calculation of transform coefficients for theworking block. The lapped transforms outperform the DCT on two counts: (i) from the analysis viewpoint, they take into account interblock correlation and hence provide better energy compaction; (ii) from the synthesis viewpoint, their overlapping basisfunctions decay asymptotically to zero at the ends, reducing blocking discontinuities dramatically.
Nevertheless, lapped transforms have not yet been able to supplant the unadorned DCT in international standard coding routines. The principal reason is that the modest improvement in coding performance available up to now has not been sufficientto justify the significant increase in computational complexity. In the prior art, therefore, lapped transforms remained too computationally complex for the benefits they provided. In particular, the previous lapped transformed somewhat reduced but didnot eliminate the annoying blocking artifacts.
It is therefore an object of the current invention to provide a new transform which is simple and fast enough to replace the bare DCT in international standards, in particular in JPEG and MPEGlike coding standards. It is another object of thisinvention to provide an image transform which has overlapping basis functions so as to avoid blocking artifacts. It is a further object of this invention to provide a lapped transform which is approximately as fast as, but more efficient for compressionthan, the bare DCT. It is yet another object of this invention to provide dramatically improved speed and efficiency using a lapped transform with lifting steps in a butterfly structure with dyadicrational coefficients. It is yet a further object ofthis invention to provide a transform structure such that for a negligible complexity surplus over the bare DCT a dramatic coding performance gain can be obtained both from a subjective and objective point of view while blocking artifacts are completelyeliminated.
SUMMARY OF THE INVENTION
In the current invention, we use a family of lapped biorthogonal transforms implementing a small number of dyadicrational lifting steps. The resulting transform, called the LiftLT, not only has high computation speed but is wellsuited toimplementation via VLSI.
Moreover, it also consistently outperforms stateoftheart wavelet based coding systems in coding performance when the same quantizer and entropy coder are used. The LiftLT is a lapped biorthogonal transform using lifting steps in a modularlattice structure, the result of which is a fast, efficient, and robust encoding system. With only 1 more multiplication (which can also be implemented with shiftandadd operations), 22 more additions, and 4 more delay elements compared to the bareDCT, the LiftLT offers a fast, lowcost approach capable of straightforward VLSI implementation while providing reconstructed images which are high in quality, both objectively and subjectively. Despite its simplicity, the LiftLT provides a significantimprovement in reconstructed image quality over the traditional DCT in that blocking is completely eliminated while at medium and high compression ratios ringing artifacts are reasonably contained. The performance of the LiftLT surpasses even that ofthe wellknown 9/7tap biorthogonal wavelet transform with irrational coefficients. The LiftLT's blockbased structure also provides several other advantages: supporting parallel processing mode, facilitating regionofinterest coding and decoding, andprocessing large images under severe memory constraints.
Most generally, the current invention is an apparatus for block coding of windows of digitally represented images comprising a chain of lattices of lapped transforms with dyadic rational lifting steps. More particularly, this invention is asystem of electronic devices which codes, stores or transmits, and decodes M.times.M sized blocks of digitally represented images, where M is an even number. The main block transform structure comprises a transform having M channels numbered 0 throughM1, half of said channel numbers being odd and half being even; a normalizer with a dyadic rational normalization factor in each of said M channels; two lifting steps with a first set of identical dyadic rational coefficients connecting each pair ofadjacent numbered channels in a butterfly configuration, M/2 delay lines in the odd numbered channels; two inverse lifting steps with the first set of dyadic rational coefficients connecting each pair of adjacent numbered channels in a butterflyconfiguration; and two lifting steps with a second set of identical dyadic rational coefficients connecting each pair of adjacent odd numbered channels; means for transmission or storage of the transform output coefficients; and an inverse transformcomprising M channels numbered 0 through M1, half of said channel numbers being odd and half being even; two inverse lifting steps with dyadic rational coefficients connecting each pair of adjacent odd numbered channels; two lifting steps with dyadicrational coefficients connecting each pair of adjacent numbered channels in a butterfly configuration; M/2 delay lines in the even numbered channels; two inverse lifting steps with dyadic rational coefficients connecting each pair of adjacent numberedchannels in a butterfly configuration; a denormalizer with a dyadic rational inverse normalization factor in each of said M channels; and a base inverse transform having M channels numbered 0 through M1.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a polyphase representation of a linear phase perfect reconstruction filter bank.
FIG. 2 shows the most general lattice structure for linear phase lapped transforms with filter length L=KM.
FIG. 3 shows the parameterization of an invertible matrix via the singular value decomposition.
FIG. 4 portrays the basic butterfly lifting configuration.
FIG. 5 depicts the analysis LiftLT lattice drawn for M=8.
FIG. 6 depicts the synthesis LiftLT lattice drawn for M=8.
FIG. 7 depicts a VLSI implementation of the analysis filter bank operations.
FIG. 8 shows frequency and time responses of the 8.times.16 LiftLT: Left: analysis bank. Right: synthesis bank.
FIG. 9 portrays reconstructed "Barbara" images at 1:32 compression ratio.
DESCRIPTION OF THE PREFERRED EMBODIMENT
Typically, a block transform for image processing is applied to a block (or window) of, for example, 8.times.8 group of pixels and the process is iterated over the entire image. A biorthogonal transform in a block coder uses as a decompositionbasis a complete set of basis vectors, similar to an orthogonal basis. However, the basis vectors are more general in that they may not be orthogonal to all other basis vectors. The restriction is that there is a "dual" basis to the originalbiorthogonal basis such that every vector in the original basis has a "dual" vector in the dual basis to which it is orthogonal. The basic idea of combining the concepts of biorthogonality and lapped transforms has already appeared in the prior art. The most general lattice for Mchannel linear phase lapped biorthogonal transforms is presented in T. D. Tran, R. de Queiroz, and T. Q. Nguyen, "The generalized lapped biorthogonal transform," ICASSP, pp. 14411444, Seattle, May 1998, and in T. D. Tran,R. L. de Queiroz, and T. Q. Nguyen, "Linear phase perfect reconstruction filter bank: lattice structure, design, and application in image coding" (submitted to EEE Trans. on Signal Processing, April 1998). A signal processing flow diagram of thiswellknown generalized filter bank is shown in FIG. 2.
In the current invention, which we call the Fast LiftLT, we apply lapped transforms based on using fast lifting steps in an Mchannel uniform linearphase perfect reconstruction filter bank, according to the generic polyphase representation ofFIG. 1. In the lapped biorthogonal approach, the polyphase matrix E(z) can be factorized as .function..times..function..times. .times..times. .times..function..times..times..function..function..function..times..function..times..PHI..times..times..LAMBDA..times..function..times..times. ##EQU00001## In these equations, I is the identity matrix, and J is the matrix with 1's on the antidiagonal.
The transform decomposition expressed by equations (1) through (3) is readily represented, as shown in FIG. 2, as a complete lattice replacing the "analysis" filter bank E(z) of FIG. 1. This decomposition results in a lattice of filters havinglength L=KM. (K is often called the overlapping factor.) Each cascading structure G.sub.1(z) increases the filter length by M. All U.sub.i and V.sub.i, i=0,1, . . . , K1, are arbitrary M/2.times.M/2 invertible matrices. According to a theorem wellknown in the art, invertible matrices can be completely represented by their singular value decomposition (SVD), given by U.sub.i=U.sub.i0.GAMMA..sub.iU.sub.i1, V.sub.i=V.sub.i0.DELTA..sub.iV.sub.i1 where U.sub.i0, U.sub.i1, V.sub.i0, V.sub.i1 arediagonalizing orthogonal matrices and .GAMMA..sub.i, .DELTA..sub.i are diagonal matrices with positive elements.
It is well known that any M/2.times.M/2 orthogonal matrix can be factorized into M(M2)/8 plane rotations .theta..sub.i and that the diagonal matrices represent simply scaling factors .alpha..sub.i. Accordingly, the most general LT latticeconsists of KM(M2)/2 two dimensional rotations and 2M diagonal scaling factors .alpha..sub.i. Any invertible matrix can be expressed as a sequence of pairwise plane rotations .theta. and scaling factors .alpha..sub.i as shown in FIG. 3.
It is also well known that a plane rotation can be performed by 3 "shears": .times. .times..theta..times. .times..theta..times. .times..theta..times. .times..theta..times. .times..theta..times. .times..theta..function..times. .times..theta..function..times. .times..theta..times. .times..theta. ##EQU00002## This can be easily verified by computation
Each of the factors above is capable of a "lifting" step in signal processing terminology. The product of two which effects a linear transform of pairs of coefficients: .fwdarw..times. ##EQU00003## The signal processing flow diagram of thisoperation is shown in FIG. 4. The crossing arrangement of these flow paths is also referred to as a butterfly configuration. Each of the above "shears" can be written as a lifting step.
Combining the foregoing, the shears referred to can be expressed as computationally equivalent "lifting steps" in signal processing. In other words, we can replace each "rotation" by 3 closelyrelated lifting steps with butterfly structure. Itis possible therefore to implement the complete LT lattice shown in FIG. 2 by 3KM(2)/2 lifting steps and 2M scaling multipliers.
In the simplest but currently preferred embodiment, to minimize the complexity of the transform we choose a small overlapping factor K=2 and set the initial stage E.sub.0 to be the DCT itself Many other coding transforms can serve for the basestage instead of the DCT, and it should be recognized that many other embodiments are possible and can be implemented by one skilled in the art of signal processing.
Following the observation in H. S. Malvar, "Lapped biorthogonal transforms for transform coding with reduced blocking and ringing artifacts," ICASSP97, Munich, April 1997, we apply a scaling factor to the first DCT's antisymmetric basis togenerate synthesis LT basis functions whose end values decay smoothly to exact zeroa crucial advantage in blocking artifacts elimination. However, instead of scaling the analysis by {square root over (2)} and the synthesis by 1/ {square root over(2)}, we opt for 25/16 and its inverse 16/25 since they allow the implementation of both analysis and synthesis banks in integer arithmetic. Another value that works almost as well as 25/16 is 5/4. To summarize, the following choices are made in thefirst stage: the combination of U.sub.00 and V.sub.00 with the previous butterfly form the DCT; .DELTA..function..times. ##EQU00004## and .GAMMA..sub.o=U.sub.00=V.sub.00=I.sub.M/2. See FIG. 2.
After 2 series of .+.1 butterflies W and the delay chain .LAMBDA.(z), the LT symmetric basis functions already have good attenuation, especially at DC (.omega.=0). Hence, we can comfortably set U.sub.1=I.sub.M/2.
As noted, V.sub.1 is factorizable into a series of lifting steps and diagonal scalings. However, there are several problems: (i) the large number of lifting steps is costly in both speed and physical realestate in VLSI implementation; (ii) thelifting steps are related; (iii) and it is not immediately obvious what choices of rotation angles will result in dyadic rational lifting multipliers. In the current invention, we approximate V.sub.1 by (M/2)1 combinations of blockdiagonalpredictandupdate lifting steps, i.e., .times. ##EQU00005##
Here, the free parameters u.sub.i and p.sub.i can be chosen arbitrarily and independently without affecting perfect reconstruction. The inverses are trivially obtained by switching the order and the sign of the lifting steps. Unlike popularlifting implementations of various wavelets, all of our lifting steps are of zeroorder, namely operating in the same time epoch. In other words, we simply use a series of 2.times.2 upper or lower diagonal matrices to parameterize the invertible matrixV.sub.1.
Most importantly, fastcomputable VLSIfriendly transforms are readily available when u.sub.i and p.sub.i are restricted to dyadic rational values, that is, rational fractions having (preferably small) powers of 2 denominators. With suchcoefficients, transform operations can for the most part be reduced to a small number of shifts and adds. In particular, setting all of the approximating lifting step coefficients to 1/2 yields a very fast and elegant lapped transform. With thischoice, each lifting step can be implemented using only one simple bit shift and one addition.
The resulting LiftLT lattice structures are presented in FIGS. 5 and 6. The analysis filter shown in FIG. 5 comprises a DCT block 1, 25/16 normalization 2, a delay line 3 on four of the eight channels, a butterfly structured set of lifting steps5, and a set of four fast dyadic lifting steps 6. The frequency and impulse responses of the 8.times.16 LiftLT's basis functions are depicted in FIG. 8.
The inverse or synthesis lattice is shown in FIG. 6. This system comprises a set of four fast dyadic lifting steps 11, a butterflystructured set of lifting steps 12, a delay line 13 on four of the eight channels, 16/25 inverse normalization 14,and an inverse DCT block 15. FIG. 7 also shows the frequency and impulse responses of the synthesis lattice.
The LiftLT is sufficiently fast for many applications, especially in hardware, since most of the incrementally added computation comes from the 2 butterflies and the 6 shiftandadd lifting steps. It is faster than the typeI fast LOT describedin H. S. Malvar, Signal Processing with Lapped Transforms, Artech House, 1992. Besides its low complexity, the LiftLT possesses many characteristics of a highperformance transform in image compression: (i) it has high energy compaction due to a highcoding gain and a low attenuation near DC where most of the image energy is concentrated; (ii) its synthesis basis functions also decay smoothly to zero, resulting in blockingfree reconstructed images.
Comparisons of complexity and performance between the LiftLT and other popular transforms are tabulated in Table 1 and Table 2. The LiftLT's performance is already very close to that of the optimal generalized lapped biorthogonal transform,while its complexity is the lowest amongst the transforms except for the DCT.
To assess the new method in image coding, we compared images coded and decoded with four different transforms: DCT: 8channel, 8tap filters TypeI Fast LOT: 8channel, 16tap filters LiftLT: 8channel, 16tap filters Wavelet: 9/7tapbiorthogonal. In this comparison, we use the same SPIHT's quantizer and entropy coder, A. Said and W. A. Pearlman, "A new fast and efficient image coder based on set partitioning in hierarchical trees," IEEE Trans on Circuits Syst. Video Tech., vol. 6,pp. 243250, June 1996, for every transform. In the blocktransform cases, we use the modified zerotree structure in T. D. Tran and T. Q. Nguyen, "A lapped transform embedded image coder," ISCAS, Monterey, May 1998, where each block of transformcoefficients is treated analogously to a full wavelet tree and three more levels of decomposition are employed to decorrelate the DC subband further.
Table 1 contains a comparison of the complexity of these four coding systems, comparing numbers of operations needed per 8 transform coefficients:
TABLEUS00001 No. Transform Multiplications No. Additions No. Shifts 8 .times. 8 DCT 13 29 0 8 .times. 16 TypeI Fast LOT 22 54 0 917 Wavelet, 1level 36 56 0 8 .times. 6 Fast LiftLT 14 51 6
In such a comparison, the number of multiplication operations dominates the "cost" of the transform in terms of computing resources and time, and number of additions and number of shifts have negligible effect. In this table, it is clear thatthe fast LiftLT is almost as low as the DCT in complexity and more than twice as efficient as the wavelet transform.
Table 2 sets forth a number of different performance measures for each of the four methods:
TABLEUS00002 DC Stopband Coding Atten. Atten. Mir. Freq. Transform Gain (dB) (dB) (dB) Atten. (dB) 8 .times. 8 DCT 8.83 310.62 9.96 322.1 8 .times. 16 TypeI Fast LOT 9.2 309.04 17.32 314.7 8 .times. 16 Optional LT 9.62 327.4 13.555.54 8 .times. 16 Fast LiftLT 9.54 312.56 13.21 304.85
The fast LiftLT is comparable to the optional 8.times.16 LT transform in coding gain and stopband attenuation an significantly better than the DCT.
Reconstructed images for a standard 512.times.512 "Barbara" test image at 1:32 compression ratio are shown in FIG. 9 for aesthetic and heuristic evaluation. Top left 21 is the reconstructed image for the 8.times.8 DCT (27.28 dB PSNR); top rightshows the result for the 8.times.16 LOT(28.71 dB PSNR); bottom left is the 9/7 tap wavelet reconstruction (27.58 dB PSNR); and bottom right, 8.times.16 LiftLT (28.93 dB PSNR). The objective coding results for standard 512.times.512 "Lena," "Goldhill,"and "Barbara" test image (PSNR in dB's) are tabulated in Table 3:
TABLEUS00003 Lena Goldhill Barbara Comp. 9/7 WL 8 .times. 8 8 .times. 16 8 .times. 16 9/7 WL 8 .times. 8 8 .times. 16 8 .times. 16 9/7 WL 8 .times. 8 8 .times. 16 8 .times. 16 Ratio SPIHT DCT LOT LiftLT SPIHT DCT LOT LiftLT SPIHT DCTLOT LiftLT 8 40.41 39.91 40.02 40.21 36.55 36.25 36.56 36.56 36.41 36.31 37.22 37.57 16 37.21 36.38 36.69 37.11 33.13 32.76 33.12 33.22 31.4 31.11 32.52 32.82 32 34.11 32.9 33.49 34 30.56 30.07 30.52 30.63 27.58 27.28 28.71 28.93 64 31.1 29.67 30.43 30.928.48 27.93 28.34 28.54 24.86 24.58 25.66 25.93 100 29.35 27.8 28.59 29.03 27.38 26.65 27.08 27.28 23.76 23.42 24.32 24.5 128 28.38 26.91 27.6 28.12 26.73 26.01 26.46 26.7 23.35 22.68 23.36 23.47
PSNR is an acronym for power signal to noise ratio and represents the logarithm of the ratio of maximum amplitude squared to the mean square error of the reconstructed signal expressed in decibels (dB).
The LiftLT outperforms its block transform relatives for all test images at all bit rates. Comparing to the wavelet transform, the LiftLT is quite competitive on smooth imagesabout 0.2 dB below on Lena. However, for more complex images suchas Goldhill or Barbara, the LiftLT consistently surpasses the 9/7tap wavelet. The PSNR improvement can reach as high as 1.5 dB.
FIG. 9 also shows pictorially the reconstruction performance in Barbara images at 1:32 compression ratio for heuristic comparison. The visual quality of the LiftLT reconstructed image is noticeably superior. Blocking is completely avoidedwhereas ringing is reasonably contained. Top left: 8.times.8 DCT, 27.28 dB. Top right: 8.times.16 LOT, 28.71 dB. Bottom left: 9/7tap wavelet, 27.58 dB. Bottom right: 8.times.16 LiftLT, 28.93 dB. Visual inspection indicates that the LiftLT codergives at least as good performance as the wavelet coder. The appearance of blocking artifacts in the DCT reconstruction (upper left) is readily apparent. The LOT transform result (upper right) suffers visibly from the same artifacts even though it islapped. In addition, it is substantially more complex and therefore slower than the DCT transform. The wavelet transform reconstruction (lower left) shows no blocking and is of generally high quality for this level of compression. It is faster thanthe LOT but significantly slower than the DCT. Finally, the results of the LiftLT transform are shown at lower right. Again, it shows no blocking artifacts, and the picture quality is in general comparable to that of the wavelet transformreconstruction, while its speed is very close to that of the bare DCT.
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