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Performing scalable lossy compression on pixel encrypted images

EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2013年第1期2013卷 1页

作者： Kang, Xiangui Peng, Anjie Xu, Xianyu Cao, Xiaochun Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China China Telecom Corp Ltd Shantou Branch Shantou 515000 Guangdong Peoples R China Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing 100093 Peoples R China

Compression of encrypted data draws much attention in recent years due to the security concerns in a service-oriented environment such as cloud computing. We propose a scalable lossy compression scheme for images having their pixel value encrypted with a standard stream cipher. The encrypted data are simply compressed by transmitting a uniformly subsampled portion of the encrypted data and some bitplanes of another uniformly subsampled portion of the encrypted data. At the receiver side, a decoder performs content-adaptive interpolation based on the decrypted partial information, where the received bit plane information serves as the side information that reflects the image edge information, making the image reconstruction more precise. When more bit planes are transmitted, higher quality of the decompressed image can be achieved. The experimental results show that our proposed scheme achieves much better performance than the existing lossy compression scheme for pixel-value encrypted images and also similar performance as the state-of-the-art lossy compression for pixel permutation-based encrypted images. In addition, our proposed scheme has the following advantages: at the decoder side, no computationally intensive iteration and no additional public orthogonal matrix are needed. It works well for both smooth and texture-rich images.

关键词： Image compression Image encryption Lossy compression Image reconstruction scalable coding

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Wavelet-based joint estimation and encoding of depth-image-based representations for free-viewpoint rendering

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2008年第6期17卷 946-957页

作者： Maitre, Matthieu Shinagawa, Yoshihisa Do, Minh N. Microsoft Corp Windows Experience Grp Redmond WA 98052 USA Siemens Med Solut Malvern PA 19355 USA Univ Illinois Beckman Inst Coordinated Sci Lab Dept Elect & Comp Engn Urbana IL 61801 USA

We propose a wavelet-based codec for the static depth-image-based representation, which allows viewers to freely choose the viewpoint. The proposed codec jointly estimates and encodes the unknown depth map from multiple views using a novel rate-distortion (RD) optimization scheme. The rate constraint reduces the ambiguity of depth estimation by favoring piece-wise-smooth depth maps. The optimization is efficiently solved by a novel dynamic programming along trees of integer wavelet coefficients. The codec encodes the image and the depth map jointly to decrease their redundancy and to provide a RD-optimized bitrate allocation between the two. The codec also offers scalability both in resolution and in quality. Experiments on real data show the effectiveness of the proposed codec.

关键词： depth estimation depth-image-based representation (DIBR) free-viewpoint rendering image-based rendering joint coding rate-distortion optimization scalable coding 3-D TV

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Performance of the color set partitioning in hierarchical tree scheme (CSPIHT) in video coding

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2001年第2期20卷 253-270页

作者： Kassim, AA Siong, LW Natl Univ Singapore Dept Elect & Comp Engn Singapore 119260 Singapore

This paper describes the implementation of the recently introduced color set partitioning in hierarchical tree (CSPIHT)-based scheme for video coding. The intra- and interframe coding performance of a CSPIHT-based video coder (CVC) is compared against that of the H.263 at bit rates lower than 64 kbit/s. The CVC performs comparably or better than the H.263 at lower bit rates, whereas the H.263 performs better than the CVC at higher bit rates. We identify areas that hamper the performance of the CVC and propose an improved scheme that yields better performance in image and video coding in low bit-rate environments.

关键词： SPIHT CSPIHT scalable coding video coding video compression discrete wavelet transform

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scalable authentication and nonrepudiation technique for JPEG 2000 images using JPSEC protection tools

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2006年第11期E89A卷 2945-2954页

作者： Haggag, Ayman Ghoneim, Mohamed Lu, Jianming Yahagi, Takashi Chiba Univ Grad Sch Sci & Technol Chiba 2638522 Japan

In this paper, we first briefly discuss the newly emerging Secured JPEG (JPSEC) standard for security services for JPEG 2000 compressed images. We then propose our novel approach for applying authentication to JPEG 2000 images in a scalable manner. Our authentication technique can be used for source authentication, nonrepudiation and integrity verification for the received possibly transcoded JPEG 2000 images in such a way that it is possible to authenticate different resolutions or different qualities extracted or received from a JPEG 2000 encoded image. Three different implementation methods for our authentication technique are presented. Packet-Based Authentication involves using the MD5 hashing algorithm for calculating the hash value for each individual packet in the JPEG 2000 codestream. Hash values are truncated to a specified length to reduce the overhead in storage space, concatenated into a single string, and then signed using the RSA algorithm and the author's private key for repudiation;prevention. Resolution-Based Authentication and Quality-Based Authentication methods involve generating a single hash value from all contiguous packets from each entire resolution or each entire quality layer, respectively. Our algorithms maintain most of the inherent flexibility and scalability of JPEG 2000 compressed images. The resultant secured codestream is still JPEG 2000 compliant and compatible with JPEG 2000 compliant decoders. Also, our algorithms are compatible with the Public Key Infrastructure (PKI) for preventing signing repudiation from the sender and are implemented using the new JPSEC standard for security signaling.

关键词： JPEG 2000 JPSEC scalable coding authentication nonrepudiation Public Key Infrastructure (PKI)

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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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Rate-distortion approach to databases: Storage and content-based retrieval

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IEEE TRANSACTIONS ON INFORMATION THEORY 2004年第6期50卷 953-967页

作者： Tuncel, E Koulgi, P Rose, K Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This paper investigates the relationship between rate-distortion theory and efficient content-based data retrieval from high-dimensional databases. We consider database design as the encoding of a data object sequence, and retrieval from the database as the decoding of the sequence using side information (i.e., the query) available only at the decoder. We show that, in this setting, the optimal asymptotic tradeoff between the search time R-s (bits per data object read from the storage device) and the expected search accuracy D-s (relevance of the retrieved data set) is given by the Wyner-Ziv solution with a side-information-dependent distortion measure. Moreover, the data indexing and retrieval problem is, in general, inseparable from the data compression problem. Data items selected by the search procedure, which can be stored in the disk with a limited total rate of R-r greater than or equal to R-s, need to be presented at a prescribed expected reconstruction quality D-r. This is, hence, a problem of scalable source coding or successive refinement, albeit with differing layer distortion measures to quantify search and reconstruction quality, respectively. We derive a single-letter characterization of all achievable quadruples {R-s, R-r, D-s, D-r}, and prove conditions for "successive refinability" without rate loss. Finally, we show that the special case D-s = D-r = 0 is nontrivial and of practical interest in this context, as it can impose "acceptable" search and reconstruction qualities for each individual data item and for the entire query space with high probability, in contradistinction with standard average distortion requirements. The region of achievable {R-s,R- R-r} is obtained by adapting Rimoldi's characterization to a new regular scalable coding problem.

关键词： approximate similarity searching content-based retrieval databases scalable coding successive refinability without rate loss Wyner-Ziv problem zero-one distortion measures

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Unified and scalable Deep Image Compression Framework for Human and Machine

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2024年第10期20卷 1-22页

作者： Zhang, Gai Zhang, Xinfeng Tang, Lv Univ Chinese Acad Sci Beijing Peoples R China

Image compression aims to minimize the amount of data in image representation while maintaining a certain visual quality for humans, which is an essential technique for storage and transmission. Recently, along with the development of computer vision, machines have become another primary receiver for images and require compressed images at a certain quality level, which may be different from that of human vision. In many scenarios, compressed images should serve both human and machine vision tasks, but few compression methods are designed for both goals simultaneously. In this article, we propose a unified and scalable deep image compression (USDIC) framework that jointly optimizes the image quality according to human and machine vision in an end-to-end style. For the encoder, we propose an information splitting mechanism (ISM) to separate images into semantic and visual features, which mainly aims at machine analysis and human viewing tasks. For the decoder, we design a scalable decoding architecture. The encoded semantic feature is first decoded for machine analysis tasks, and the image is decoded and reconstructed further by leveraging the decoded semantic features. Herein, to further remove the redundancy between the semantic and visual features of images, we propose a scalable entropy model (SEM) with a joint optimization strategy to reconstruct the image using the two kinds of decoded features. Extensive experimental results show that the proposed USDIC achieves much better performance on the image analysis task while maintaining competitive performance on the traditional image reconstruction task compared with popular image compression methods.

关键词： Deep-learning based image compression image coding for machine scalable coding

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scalable Compression of Stream Cipher Encrypted Images Through Context-Adaptive Sampling

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2014年第11期9卷 1857-1868页

作者： Zhou, Jiantao Au, Oscar C. Zhai, Guangtao Tang, Yuan Yan Liu, Xianming Univ Macau Fac Sci & Technol Dept Comp & Informat Sci Macau Peoples R China UMacau Zhuhai Res Inst Zhuhai 519080 Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Shanghai 200030 Peoples R China Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China

This paper proposes a novel scalable compression method for stream cipher encrypted images, where stream cipher is used in the standard format. The bit stream in the base layer is produced by coding a series of nonoverlapping patches of the uniformly down-sampled version of the encrypted image. An off-line learning approach can be exploited to model the reconstruction error from pixel samples of the original image patch, based on the intrinsic relationship between the local complexity and the length of the compressed bit stream. This error model leads to a greedy strategy of adaptively selecting pixels to be coded in the enhancement layer. At the decoder side, an iterative, multiscale technique is developed to reconstruct the image from all the available pixel samples. Experimental results demonstrate that the proposed scheme outperforms the state-of-the-arts in terms of both rate-distortion performance and visual quality of the reconstructed images at low and medium rate regions.

关键词： Signal processing in encrypted domain scalable coding image compression adaptive sampling

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Motion-compensated video compression with reduced complexity encoding for remote transmission

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2001年第7期16卷 627-642页

作者： Creusere, CD New Mexico State Univ Klipsch Sch Elect & Comp Engn Las Cruces NM 88003 USA USN Air Warfare Ctr China Lake CA USA

Efficient operation at very low bit-rates necessitates a complex encoder that can exploit both spatial and temporal redundancy in a video sequence. To reduce the complexity of such an encoder, we introduce here a new form of motion compensation similar to the conventional hybrid DPCM-transform method but where the compensation is performed outside the feedback loop. In addition to reducing encoder complexity, the proposed out-of-loop (OOL) compensation scheme also supports resolution and frame-rate scalability. While the basic idea is conceptually similar to the pan compensation proposed by Taubman and Zakhor, our method continually tracks and updates the image in the feedback loop in the same way as the conventional DPCM coder. Using OOL compensation, we have observed an average encoder speed increase of 33% on a typical CIF-size video sequence compared to the conventional approach with no significant decrease in decoder speed. Furthermore, we have also found that OOL pan compensation significantly improves the rate-distortion performance of the system relative to conventional pan compensation - taken over five different video sequences, the average bit-rate reduction is 9.2% and the average mean-squared error reduction is 29.6%. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： image compression video compression motion compensation low complexity wavelet scalable coding

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Sparse representations for spatial prediction and texture refinement

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2011年第8期22卷 712-720页

作者： Martin, Aurelie Fuchs, Jean-Jacques Guillemot, Christine Thoreau, Dominique Univ Rennes 1 IRISA F-35042 Rennes France Technicolor Res & Innovat Labs F-35510 Cesson Sevigne France

In this work, we propose a novel approach for signal prediction based on the use of sparse signal representations and Matching Pursuit (MP) techniques. The paper first focuses on spatial texture prediction in a conventional block-based hybrid coding scheme and secondly addresses inter-layer prediction in a scalable video coding (SVC) framework. For spatial prediction the signal reconstruction of the block to predict is based on basis functions selected with the MP iterative algorithm, to best match a causal neighborhood. Inter-layer MP based prediction employs base layer upsampled components additionally to the causal neighborhood in order to improve the representation of high frequencies. New solutions are proposed for efficiently deriving and exploiting the atoms dictionary through phase refinement and mono-dimensional basis functions. Experimental results indicate noticeable improvement of rate/distortion performance compared to the standard prediction methods as specified in H.264/AVC and its extension SVC. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Spatial prediction H.264/AVC Sparse representations Extrapolation Phase refinement Video compression scalable coding Redundant dictionaries

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