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A novel statistical distortion model based on mixed Laplacian and uniform distribution of Mpeg-4 FGS

JOURNAL OF RESEARCH AND PRACTICE IN INFORMATION TECHNOLOGY 2006年第3期38卷 267-277页

作者： Li, Xie Zhang, Wenjun Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Shanghai 200030 Peoples R China

The Laplacian Distribution has been widely used to characterize the distribution of DCT coefficients in a great deal of research on statistical attributes of DCT for the reason that Laplacian distribution can achieve a good balance between the simplification of the model and fidelity to the real empirical data. But in our research, we found that there is a large discrepancy between the real data and the distortion model based on Laplacian distribution. Furthermore, the higher the rate, the larger the distortion. In this paper we proposed a new distortion model based on mixed Laplacian and Uniform distributions. Experimental results show that the MLQ distortion model can approximate the real empirical data and has a higher degree of accuracy than the conventional distortion model based on Laplacian distribution. Compared with the conventional distortion model based on Laplacian distribution, the new model can decrease the MSE distortion by 2-6 units. The MLQ distortion model can represent the relationship of rate and distortion of the Mpeg-4 FGS enhancement layer with a higher degree of accuracy.

关键词： Mpeg 4 FGS bit plane scalable coding distortion statistical model

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Priors Guided Extreme Underwater Image Compression for Machine Vision and Human Vision

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IEEE JOURNAL OF OCEANIC ENGINEERING 2023年第3期48卷 888-902页

作者： Fang, Zhengkai Shen, Liquan Li, Mengyao Wang, Zhengyong Jin, Yanliang Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China Shanghai Univ Key Lab Specialty Fiber Opt & Opt Access Networks Joint Int Res Lab Specialty Fiber Opt & Adv Commun Shanghai 200444 Peoples R China

A low bit-rate compression is required for underwater images due to the limited bandwidth in underwater acoustic communication, which limits performances of both machine analysis and human perception in most underwater applications. Few existing compression methods consider the unique characteristics of underwater images such as color shift and haze effect to better fulfill requirements of various applications under low bit-rates. To address this problem, we propose a novel extreme underwater image compression framework, which can provide scalability to support machine vision and human vision with the assistance of underwater priors. Specifically, the base layer is composed of a feature extractor and a generator, where global structural edges and high-level features of regions with a significant impact on machine analysis are extracted and used for reconstructing a feature-matching image for analysis purpose. Considering the negative influence of underwater imaging processes on machine vision, in this article, a feature degradation removal module guided by underwater priors is proposed to alleviate feature-level degradation via taking analysis-friendly enhanced images as auxiliary information. As for the enhancement layer aiming for human vision, the residual between the original image and the reconstruction from base layer is compressed. A feature attention block and a background light recovery block are designed utilizing features extracted from enhanced images and the underwater before further recovering the original scene with a good perception quality under low bit-rates. Experimental results demonstrate the superiority of our framework in both machine vision tasks and perception quality compared with traditional compression methods and learned-based methods.

关键词： Feature enhance generative compression scalable coding underwater image compression

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A scalable wideband speech codec using the wavelet packet transform based on the internet low bitrate codec

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COMPUTER SPEECH AND LANGUAGE 2019年 54卷 61-70页

作者： Seto, Koji Ogunfunmi, Tokunbo Santa Clara Univ Dept Elect Engn Santa Clara CA 95053 USA

Most recent speech codecs employ code excited linear prediction (CELP) and transmit side information to improve speech quality under packet loss. Another approach to achieve high robustness to packet loss is to use the frame independent coding scheme based on the internet low bitrate codec (iLBC). The scalable wideband speech codec based on the iLBC was previously presented and outperformed G.729.1 at most bit rates according to the objective quality. This paper presents improvements to the previous work. Specifically, we employ the wavelet packet transform (WPT) instead of the modified discrete cosine transform (MDCT) to enhance the quality, and evaluate the proposed codec based on both the objective and subjective quality measures. The objective quality evaluation results show that clear improvement is achieved and that the proposed codec outperforms G.729.1 at the bit rate of 18 kbps or higher under clean channel conditions and has higher robustness to packet loss than G.729.1. The informal subjective test results also show similar trends. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Wavelet packet transform (WPT) Internet low bitrate codec (iLBC) Packet loss scalable coding Speech coding Voice over Internet protocol (VoIP)

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Improving SPIHT using virtual encapsulation

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2004年第6期23卷 507-516页

作者： Kassim, AA SeeToh, CW Natl Univ Singapore Dept Elect & Comp Engn Singapore 119260 Singapore

In this paper, we propose a procedure that enhances the very low bit-rate coding performance of Set Partitioning in Hierarchical Trees (SPIHT)-based image coders. In SPIHT-based algorithms, all nodes with descendants in the LL band are initially added to the list of insignificant sets as type-A entries. Our experiments indicate that type-A nodes are highly likely to be insignificant during the sorting passes of the high bit planes. Our new procedure exploits this characteristic so that all these type-A nodes can be encapsulated into a single virtual node.

关键词： SPIET CSPIHT scalable coding virtual encapsulation

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Enhancement Layer coding for Chroma Sub-Sampled Screen Content Video

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年第2期32卷 788-801页

作者： Heindel, Andreas Prestele, Benjamin Gehlert, Alexander Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg FAU Inst Multimedia Commun & Signal Proc D-91058 Erlangen Germany LogMeIn Inc D-01067 Dresden Germany

Prevalent video codec implementations deployed in the field often solely support chrominance sub-sampled video data represented by the YCbCr 4:2:0 format. For certain applications like screen sharing, however, chroma sub-sampling leads to disturbing artifacts, especially for text or graphics with thin lines. It is desirable to reduce these artifacts while maintaining compatibility with all user devices. For this reason, an enhancement layer coding framework for chroma-format scalable coding with specific focus on screen content is proposed in this paper. Based on an analysis of screen content data characteristics, the enhancement layer codec is optimized specifically for this content class, is of low algorithmic complexity, and applicable with any image or video codec for base layer compression in a joint coding system. The system is intentionally not designed as a general purpose lossless YCbCr 4:4:4 coding scheme, but instead chooses to close a quality gap that prevalent video codecs do not address. Experimental analysis reveals an average BD-PSNR gain in the RGB domain of 1.0 dB comparing the proposed two-layer scalable coding approach to single layer compression using base layer coding only. In relation to simulcast coding, an average BDR RGB difference of 8.1% is observed.

关键词： Encoding Decoding Standards Video codecs Image coding Hardware Receivers Video coding chroma sub-sampling scalable coding enhancement layer HEVC

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Evaluation of Asymmetric Stereo Video coding and Rate Scaling for Adaptive 3D Video Streaming

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IEEE TRANSACTIONS ON BROADCASTING 2011年第2期57卷 593-601页

作者： Saygili, Gorkem Gurler, Cihat Goktug Tekalp, A. Murat Koc Univ Coll Engn Istanbul Turkey

It is well known that the human visual system can perceive high frequencies in 3D stereo video, even if that information is present in only one of the views. Therefore, the best perceived 3D stereo video quality may be achieved by asymmetric coding where the reference and auxiliary (right and left) views are coded at unequal PSNR. However, the questions of what is the best level of asymmetry in order to maximize the perceived quality and whether asymmetry should be achieved by spatial resolution reduction or PSNR (quality) reduction have been open issues. We conducted extensive subjective tests, which indicate that if the reference view is encoded at sufficiently high quality and the auxiliary view is encoded at a lower quality but above a certain PSNR threshold, then the degradation in 3D video quality is unnoticeable. Since asymmetric coding by PSNR reduction gives finer control over achievable PSNR values over spatial resolution reduction, asymmetry by PSNR reduction allows us to encode at a point more close to this just-noticeable asymmetry PSNR threshold;hence will be preferred over the spatial resolution reduction method. Subjective tests also indicate that below this just-noticeable asymmetry threshold, where subtle artifacts start to appear, symmetric coding performs better than asymmetric coding in terms of perceived 3D video quality. Therefore, we show that the choice between asymmetric vs. symmetric coding depends on PSNR;hence, the available total bitrate. This paper also proposes a novel asymmetric scalable stereo video coding framework to enable adaptive stereoscopic video streaming taking full advantage of these observations and subjective test results.

关键词： Adaptive streaming scalable coding stereo rate adaptation stereo video 3D video quality evaluation

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Delay-constrained transmission of fine scalable coded content over P2P networks

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2005年第1期20卷 21-37页

作者： Su, X Shang, Y Wang, T Mai, YQ San Jose State Univ Dept Commun Engn San Jose CA 95192 USA Univ Missouri Dept Comp Sci Columbia MO 65211 USA Synopsys Inc Mountain View CA 94043 USA

Images or videos are generally coded before transmission, and they can be either non-scalable coded or scalable coded, which can be further classified into fine-scalable coded and coarse-scalable coded. In this paper, we focus on delivery of fine-scalable coded content. The objective of our work is to design algorithms to optimize the quality of fine-scalable coded images or videos on peer-to-peer networks when a requesting peer is delay-sensitive and has to display content within a certain delay bound. Fine-scalable coding has two properties: (1) it embeds lower bit-rate bitstreams into higher bit-rate bitstreams;and (2) its coding quality increases with every additional bit in the coded bitstream. These imply that for a given requesting peer, there may exist a dynamic set of supplying peers that have the same content coded in different bit-rates, have different outgoing bandwidth and may finish transmission at different times. In this paper, we first illustrate the importance of peer assignment problem using an example. Then we formally define and formulate the problem as two integer programming problems, from which we derive an optimal peer assignment solution. Finally, we carry out extensive experiments to verify the excellent performance of the proposed peer assignment algorithms by comparing with other heuristic schemes. (C) 2004 Elsevier B.V. All rights reserved.

关键词： image transmission scalable coding peer to peer networks, peer assignment

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Semantics-to-Signal scalable Image Compression with Learned Revertible Representations

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2021年第9期129卷 2605-2621页

作者： Liu, Kang Liu, Dong Li, Li Yan, Ning Li, Houqiang Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China

Image/video compression and communication need to serve both human vision and machine vision. To address this need, we propose a scalable image compression solution. We assume that machine vision needs less information that is related to semantics, whereas human vision needs more information that is to reconstruct signal. We then propose semantics-to-signal scalable compression, where partial bitstream is decodeable for machine vision and the entire bitstream is decodeable for human vision. Our method is inspired by the scalable image coding standard, JPEG2000, and similarly adopts subband-wise representations. We first design a trainable and revertible transform based on the lifting structure, which converts an image into a pyramid of multiple subbands;the transform is trained to make the partial representations useful for multiple machine vision tasks. We then design an end-to-end optimized encoding/decoding network for compressing the multiple subbands, to jointly optimize compression ratio, semantic analysis accuracy, and signal reconstruction quality. We experiment with two datasets: CUB200-2011 and FGVC-Aircraft, taking coarse-to-fine image classification tasks as an example. Experimental results demonstrate that our proposed method achieves semantics-to-signal scalable compression, and outperforms JPEG2000 in compression efficiency. The proposed method sheds light on a generic approach for image/video coding for human and machines.

关键词： Deep learning Image compression Lifting structure Machine vision scalable coding

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An end-to-end adaptation protocol for layered video multicast using optimal rate allocation

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IEEE TRANSACTIONS ON MULTIMEDIA 2004年第1期6卷 87-102页

作者： Liu, JC Li, B Zhang, YQ Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci Kowloon Hong Kong Peoples R China Microsoft Res Beijing Peoples R China

Layered transmission is a promising solution to video multicast over the heterogeneous Internet. However, since the number of layers is practically limited, noticeable mismatches would occur between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers. In this paper, we show that such mismatch can be effectively reduced using a dynamic and fine-grained layer rate allocation on the sender's side. Specifically, we study the optimization criteria for rate allocation, and propose a metric called Application-aware Fairness Index. This metric takes into consideration 1) the nonlinear relation between the perceived video quality and the delivered rate and 2) the degree of satisfaction for receivers with heterogeneous bandwidth requirements. We formulate the rate allocation into an optimization problem with the objective of maximizing the expected fairness index for all receivers in a multicast session. We then derive an efficient and scalable solution, and demonstrate that it can be seamlessly integrated into an end-to-end adaptation protocol, called Hybrid Adaptation Layered Multicast (HALM). This protocol takes advantage of the emerging fine-grained layered coding, and is fully compatible with the best-effort Internet infrastructure. Simulation and numerical results show that HALM noticeably improves the degree of fairness, and interacts with TCP traffic better than static allocation based protocols. More important, increasing the number of layers in HALM generally improves the degree of fairness;it is sufficient to obtain satisfactory performance with a small number of layers (three to five layers).

关键词： rate allocation scalable coding TCP-friendliness video multicast

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Progressive coding of 3-D objects based on overcomplete decompositions

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2006年第11期16卷 1338-1349页

作者： Tosic, Ivana Frossard, Pascal Vandergheynst, Pierre Ecole Polytech Fed Lausanne Signal Proc Inst CH-1015 Lausanne Switzerland

This paper presents a progressive coding scheme for 3-D objects, based on overcomplete signal expansions on the 2-D sphere. Due to increased freedom in the basis construction, redundant expansions have shown interesting approximation properties in the decomposition of signals with multidimensional singularities organized along embedded submanifolds. We propose to map simple 3-D models on 2-D spheres and then to decompose the signal over a redundant dictionary of oriented and anisotropic atoms living on the sphere. The signal expansion is computed iteratively with a matching pursuit algorithm, which greedily selects the most prominent components of the 3-D model. The decomposition therefore inherently represents a progressive stream of atoms, which is advantageously used in the design of scalable representations. An encoder is proposed that compresses the stream of atoms by adaptive coefficient quantization and entropy coding of atom indexes. Experimental results show that the novel coding strategy outperforms state-of-the-art progressive coders in terms of distortion, mostly at low bit rates. Furthermore, since the dictionary is built on structured atoms, the proposed representation simultaneously offers an increased flexibility for easy stream manipulations. We finally illustrate that advantage in the design of a view-dependent transmission scheme.

关键词： matching pursuit progressive coding scalable coding sparse approximations 3-D model compression 3-D representation and coding

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