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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Kojima, Hiroki Koiso, Ryota Watanabe, Ryosuke Nonaka, Keisuke KDDI Research Inc. Japan

ISBN: (纸本)9798350368741

An object wave is a suitable intermediate representation format for transmitting holographic application data because it is compatible with various playback devices. However, compressing the phase component of the object wave presents challenges due to its unique signal characteristics, i.e., periodicity and randomness. Hence, object waves significantly differ from ordinary 2D images such as camera-captured and screen pictures. To overcome the challenges, we propose a conversion method for lossless phase image coding using differential pulse-code modulation. Specifically, we calculate phase differences using adjacent pixels in two directions, considering periodic cycles of 2π, and then input them into the existing image coding. This method ensures robustness against randomness by smoothing the phase difference using the average of adjacent pixels. Experimental results show that lossless phase coding with the proposed conversion method achieves coding efficiency improvements of 6.50 % over lossless phase coding without the proposed method. © 2025 IEEE.

关键词： Computer-generated hologram Differential pulse-code modulation lossless image coding Object wave data

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A two-layered wavelet-based algorithm for efficient lossless and lossy image compression

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2000年第7期10卷 1094-1102页

作者： Marpe, D Blättermann, G Ricke, J Maass, P Heinrich Hertz Inst Commun Technol Image Proc Dept Berlin Germany Humboldt Univ Charite Dept Radiol Berlin Germany Univ Bremen Dept Math Bremen Germany

In this paper, we propose a wavelet-based image-coding scheme allowing lossless and lossy compression, simultaneously, Our two-layered approach utilizes the best of two worlds: it uses a highly performing wavelet-based or wavelet packet-based coding technique for lossy compression in the low bit range as a first stage. For the second (optional) stage, we extend the concept of reversible integer wavelet transforms to the more flexible class of adaptive reversible integer wavelet packet transforms which are based on the generation of a whole library of bases, from which the best representation for a given residue between the reconstructed lossy compressed image and the original image is chosen using a fast-search algorithm. We present experimental results demonstrating that our compression algorithm yields a rate-distortion performance similar or superior to the best currently published pure lossy still image-coding methods, At the same time, the lossless compression performance of our two-layered scheme is comparable to that of state-of-the-art pure lossless image-coding schemes. Compared to other combined lossy/lossless coding schemes such as the emerging JPEG-2000 still image-coding standard PSNR improvements up to 3 dB are achieved for a set of standard test images.

关键词： best-basis algorithm lossless image coding lossy image compression wavelet transform

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LAR-LLC: A Low-Complexity Multiresolution lossless image Codec

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2016年第8期26卷 1490-1501页

作者： Liu, Yi Deforges, Olivier Samrouth, Khouloud Natl Inst Appl Sci Rennes Dept Elect & Comp Engn F-35700 Rennes France Lebanese Univ Fac Business Adm Beirut Lebanon

This paper presents a new scalable locally adaptive resolution lossless low-complexity (LAR-LLC) image codec. It is based on the LAR framework that is a multiresolution compression method supporting both lossy and lossless coding. To achieve an efficient low-complexity solution, each processing stage of the LAR is modified. For the first step, consisting of a pyramidal decomposition, a new reversible transform called hierarchical diagonal S transform (HD-ST) is proposed. The HD-ST operates on sets of data pairs, requiring only shift and add/sub operations. The second step performs the prediction of the transformed coefficients. The prediction scheme considers both inter-and intra-level information, and involves fixed weights. Then, a classification process is introduced to separate prediction errors into subclasses, using a context modeling approach. Finally, each subclass is coded by the Huffman coding algorithm. The results of the lossless compression experiments showed that LAR-LLC achieves the same compression performance as JPEG2000 with a lower complexity.

关键词： lossless image coding low complexity reversible transform scalable coding

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lossless compression of color map images by context tree modeling

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IEEE TRANSACTIONS ON image PROCESSING 2007年第1期16卷 114-120页

作者： Akimov, Alexander Kolesnikov, Alexander Franti, Pasi Univ Joensuu FI-80101 Joensuu Finland

Significant lossless compression results of color map images have been obtained by dividing the color maps into layers and by compressing the binary layers separately using an optimized context tree model that exploits interlayer dependencies. Even though the use of a binary alphabet simplifies the context tree construction and exploits spatial dependencies efficiently, it is expected that an equivalent or better result would be obtained by operating directly on the color image without layer separation. In this paper, we extend the previous context-tree-based method to operate on color values instead of binary layers. We first generate an n-ary context tree by constructing a complete tree up to a predefined depth, and then prune out nodes that do not provide compression improvements. Experiments show that the proposed method outperforms existing methods for a large set of different color map images.

关键词： context tree compression lossless image coding map image coding

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Performance impact of parameter tuning on the CCSDS-123 lossless multi- and hyperspectral image compression standard

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JOURNAL OF APPLIED REMOTE SENSING 2013年第1期7卷

作者： Auge, Estanislau Enrique Sanchez, Jose Kiely, Aaron Blanes, Ian Serra-Sagrista, Joan Univ Autonoma Barcelona Dept Informat & Commun Engn UAB E-08193 Barcelona Spain CALTECH Jet Prop Lab NASA Pasadena CA 91109 USA

Multi-spectral and hyperspectral image data payloads have large size and may be challenging to download from remote sensors. To alleviate this problem, such images can be effectively compressed using specially designed algorithms. The new CCSDS-123 standard has been developed to address onboard lossless coding of multi-spectral and hyperspectral images. The standard is based on the fast lossless algorithm, which is composed of a causal context-based prediction stage and an entropy-coding stage that utilizes Golomb power-of-two codes. Several parts of each of these two stages have adjustable parameters. CCSDS-123 provides satisfactory performance for a wide set of imagery acquired by various sensors;but end-users of a CCSDS-123 implementation may require assistance to select a suitable combination of parameters for a specific application scenario. To assist end-users, this paper investigates the performance of CCSDS-123 under different parameter combinations and addresses the selection of an adequate combination given a specific sensor. Experimental results suggest that prediction parameters have a greater impact on the compression performance than entropy-coding parameters. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： remote sensing lossless image coding predictive coding multi- and hyperspectral imagery CCSDS 123.0-B-1 configuration parameters

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Improved lossless intra coding for H.264/MPEG-4 AVC

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IEEE TRANSACTIONS ON image PROCESSING 2006年第9期15卷 2610-2615页

作者： Lee, Yung-Lyul Han, Ki-Hun Sullivan, Gary J. Sejong Univ Dept Comp Engn Seoul 143747 South Korea Microsoft Corp Redmond WA 98052 USA

A new lossless intra coding method based on sample-by-sample differential pulse code modulation (DPCM) is presented as an enhancement of the H.264[MPEG-4 AVC standard. The H.264/AVC design includes a multidirectional spatial prediction method to reduce spatial redundancy by using neighboring samples as a prediction for the samples in a block of data to be encoded. In the new lossless;intra coding method, the spatial prediction is performed based on samplewise DPCM instead of in the block-based manner used in the current H.264/AVC standard, while the block structure is retained for the residual difference entropy coding process. We show that the new method, based on samplewise DPCM, does not have a major complexity penalty, despite its apparent pipeline dependencies. Experiments show that the new lossless intra coding method reduces the bit rate by approximately 12% in comparison with the lossless;intra coding method previously included in the H.264/AVC standard. As a result, the new method is currently being adopted into the H.264/AVC standard in a new enhancement project.

关键词： AVC differential pulse code modulation (DPCM) H.264 intra coding lossless image coding lossless video coding MPEG-4 spatial prediction

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Improvements to the JPEG-LS prediction scheme

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image AND VISION COMPUTING 2004年第1期22卷 9-14页

作者： Bedi, S Edirisinghe, EA Grecos, G Loughborough Univ Technol Dept Comp Sci Loughborough LE11 3TU Leics England Loughborough Univ Technol Dept Elect & Elect Engn Loughborough LE11 3TU Leics England

In JPEG-LS, simple edge detection techniques are used in determining the predictive value of each pixel. These techniques only detect horizontal/vertical edges and have only been optimized for the prediction of pixels in the locality of such edges. Thus, JPEG-LS produces large prediction errors in the locality of diagonal edges. We propose a low complexity technique that accurately detects diagonal edges and efficiently predicts pixels, based on the information available within the standard predictive template of JPEG-LS. We show that the proposed technique outperforms JPEG-LS in terms of predicted mean squared error, by margins of up to 15%. (C) 2003 Elsevier B.V. All rights reserved.

关键词： JPEG-LS lossless image coding predictive coding edge detection

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A binary wavelet decomposition of binary images

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IEEE TRANSACTIONS ON image PROCESSING 1996年第12期5卷 1637-1650页

作者： Swanson, MD Tewfik, AH Department of Electrical Engineering University of Minnesota Minneapolis MN USA

We construct a theory of binary wavelet decompositions of finite binary images, The new binary wavelet transform uses simple modulo-2 operations. It shares many of the important characteristics of the real wavelet transform, In particular, it yields an output similar to the thresholded output of a real wavelet transform operating on the underlying binary image. We begin by introducing a new binary field transform to use as an alternative to the discrete Fourier transform over GF(2). The corresponding concept of sequence spectra over GF(2) is defined. Using this transform, a theory of binary wavelets is developed in terms of two-band perfect reconstruction filter banks in GF(2). By generalizing the corresponding real field constraints of bandwidth, vanishing moments, and spectral content in the filters, we construct a perfect reconstruction wavelet decomposition, We also demonstrate the potential use of the binary wavelet decomposition in lossless image coding.

关键词： Binary images wavelets wavelet transforms Filters lossless image coding perfect reconstruction Binary

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Wavelet coding of volumetric medical images for high throughput and operability

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2005年第6期24卷 719-727页

作者： Wu, XL Qiu, T McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4M2 Canada ATI Technol Inc Markham ON L3T 7X6 Canada

This paper presents a new three-dimensional (3-D) wavelet-based scalable lossless coding scheme for compression of volumetric medical images. Aiming to improve the productivity of radiologists and the cost-effectiveness of the system, we strive to achieve high decoder throughput, random access to coded data volume, progressive transmission, and high compression ratio in a balanced design approach. These desirable functionalities are realized by a modified 3-D dyadic wavelet transform tailored to volumetric medical images and an optimized Rice code of very low complexity.

关键词： context modeling Golomb-Rice code lossless image coding progressive transmission random access (region of interest) teleradiology 3-D wavelet transform

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Multiplierless lifting-based fast X transforms derived from fast Hartley transform factorization

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MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2018年第1期29卷 99-118页

作者： Suzuki, Taizo Kyochi, Seisuke Tanaka, Yuichi Ikehara, Masaaki Univ Tsukuba Fac Engn Informat & Syst Tsukuba Ibaraki Japan Univ Kitakyushu Dept Informat & Media Engn Kitakyushu Fukuoka Japan Tokyo Univ Agr & Technol Grad Sch BASE Koganei Tokyo Japan Keio Univ Dept Elect & Elect Engn Yokohama Kanagawa Japan

This paper presents M-channel (M = 2(N), N is an element of N, N >= 1) multiplierless liftingbased (ML-) fast X transforms (FXTs), where X = F (Fourier), C (cosine), S (sine), and H (Hartley), i. e., FFT, FCT, FST, and FHT, derived from FHT factorization as way of lowering the cost of signal (image) processing. The basic forms of ML-FXTs are described. Then, they are customized for efficient image processing. The customized ML-FFT has a real-valued calculation followed by a complex-valued one. The ML-FCT customization for a block size of 8, which is a typical size for image coding, further reduces computational costs. We produce two customized ML-FCTs for lossy and lossless image coding. Numerical simulations show that ML-FFT and ML-FCTs perform comparably to the conventional methods in spite of having fewer operations.

关键词： factorization image processing lossless image coding Fasting Transform Hartley transform

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