Redefined Block-Lifting-Based Filter Banks With Efficient Reversible Nonexpansive Convolution

Suzuki, Taizo; Tanaka, Naoki; Kudo, Hiroyuki

doi:10.1109/tcsvt.2018.2849101

Cited by 4 publications

(4 citation statements)

References 35 publications

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“…Finally, the new reversible ITI filter for lossless compression from this study is the exact-reconstruction filter set that uses the hbp6 filter. This exact-reconstruction filter set consists of 2 lifting steps -the first lift step given by (11) and the second lifting step given by (13), and a scaling factor K = Fig. 9(b), where the frequency response of the 13/11 filters using (12) for the low-pass filter lifting step is also shown for comparison.…”

Section: New Reversible Iti Filters For Lossless Compressionmentioning

confidence: 99%

“…An easily accepted and thus widely used intuitive conjecture is that for a parent transform that has high compression performance for lossy compression, if, at the same time, fewer rounding approximations are made in constructing the reversible ITI version so that it is closer to the parent transform, then, the resulting ITI transform would have high compression performance for lossless compression [14], [15]. This leads to using the design method for lossy transform in designing the parent transform for ITI lossless compression, for example, using the method of optimizing the coding gain [16] for constructing the parent transform [11]. Using this method, some high-performance ITI filterbanks were found [11].…”

Section: Introductionmentioning

confidence: 99%

“…This leads to using the design method for lossy transform in designing the parent transform for ITI lossless compression, for example, using the method of optimizing the coding gain [16] for constructing the parent transform [11]. Using this method, some high-performance ITI filterbanks were found [11]. Nevertheless, some important features exclusively for reversible ITI filters on lossless compression were ignored.…”

Section: Introductionmentioning

confidence: 99%

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Reversible Integer-to-Integer Wavelet Filter Design for Lossless Image Compression

Lin

2020

IEEE Access

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In this paper, factors that influence the lossless compression efficiency of reversible integer-tointeger (ITI) wavelet filters are presented. It is observed that there is a converged region for the bitrate of the compressed subbands. Reaching the converged region, the bitrate increment is equal to log 2 K bps, where K is the increment in ratio of the coefficient magnitude mean. The advantages of the 5/3 filters for lossless compression are then clearly explained. A new quantity, R mn , which measures the efficiency of reversible ITI transforms on flat spectrum inputs, is defined and is used in the new reversible filter design. First, keeping the distinctive merits of the 5/3 filters for lossless compression, the half-band product filter series of the Daubechies wavelet series is selected as the analysis high-pass filters. Next, the analysis low-pass filter is found by experimentally minimizing the R mn value. Finally, it is determined that the 17/11 filters, which employ the half-band product filter with 6 vanishing moments, have the highest compression efficiency. Coding results show that the new 17/11 filters lead to a bitrate reduction of 1.7% over the 5/3 filters for lossless image compression. With further enhancements on the transform part and combining the enhanced transform with more efficient entropy coding, bitrate reductions of about 3.1% and 4% respectively over the state-of-the-art lossless compression algorithms JPEG-LS and JPEG2000 lossless mode are achieved.

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Section: New Reversible Iti Filters For Lossless Compressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reversible Integer-to-Integer Wavelet Filter Design for Lossless Image Compression

Lin

2020

IEEE Access

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“…The additional signal processing can be performed reversibly as well: one example is the filtering process done through filter banks and wavelet transforms. It remains reversible as all components of signals are preserved, if nothing then as the remainder [15]. Both the reversible wavelet computation and reversible Fast Fourier Transform use the lifting scheme.…”

Section: B Digital Processingmentioning

confidence: 99%

Reversible Hardware for Acoustic Communications

2020

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Reversible computation has been recognised as a potential solution to the technological bottleneck in the future of computing machinery. Rolf Landauer determined the lower limit for power dissipation in computation and noted that dissipation happens when information is lost, i.e., when a bit is erased. This meant that reversible computation, conserving information conserves energy as well, and as such can operate on arbitrarily small power. There were only a few applications and use cases of reversible computing hardware. Here we present a novel reversible computation architecture for time reversal of waves, with an application to sound wave communications. This energy efficient design is also a natural one, and it allows the use of the same hardware for transmission and reception at the time reversal mirror.

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Efficient Rationalization of Triplet Halfband Filter Banks and its Application to Image Compression

Gawande

Rahulkar

Holambe

2020

IEEE Trans. Circuits Syst. Video Technol.

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Redefined Block-Lifting-Based Filter Banks With Efficient Reversible Nonexpansive Convolution

Cited by 4 publications

References 35 publications

Reversible Integer-to-Integer Wavelet Filter Design for Lossless Image Compression

Reversible Integer-to-Integer Wavelet Filter Design for Lossless Image Compression

Reversible Hardware for Acoustic Communications

Efficient Rationalization of Triplet Halfband Filter Banks and its Application to Image Compression

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