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Rate-distortion methods for image and video compression

IEEE SIGNAL PROCESSING MAGAZINE 1998年第6期15卷 23-50页

作者： Ortega, A Ramchandran, K Univ So Calif Dept Elect Engn Syst Integrated Media Syst Ctr Los Angeles CA 90089 USA

In this article we provide an overview of rate-distortion (R-D)based optimization techniques and their practical application to imageand video coding. We begin with a short discussion of classicalrate-distortion theory and then we show how in many practical codingscenarios, such as in standards-compliant coding environments, resourceallocation can be put in an R-D framework. We then introduce two populartechniques for resource allocation, namely, Lagrangian optimization anddynamic programming. After a discussion of these techniques as well assome of their extensions, we conclude with a quick review of literaturein these areas citing a number of applications related to image andvideo compression and transmission

关键词： data compression image coding optimisation rate distortion theory reviews video coding Lagrangian optimization coding dynamic programming image compression optimization techniques rate-distortion methods resource allocation review standards-compliant cod Video coding Rate distortion image compression Rate distortion theory Resource utilization image coding Data compression management of resources coding Video compression dynamic programming

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Design and Hardware Architecture of High-Order Conditional Entropy coding for images

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1992年第2期2卷 176-186页

作者： Lei, Shaw-Min Sun, Ming-Ting Tzou, Kou-Hu BELLCORE Red Bank NJ 07701 USA Comsat Labs Clarksburg MD 20871 USA

The advantage of employing high-order conditional probability for entropy coding has been indicated in Shannon's information theory. Some studies have shown that the improvement In coding efficiency by high-order conditional entropy coding is substantial. Nevertheless, high-order conditional entropy coding has not been practical due to its high complexity and lack of hardware to extract the conditioning state efficiently. In this paper, we adopt the recently developed incremental-tree-extension technique to design the conditional tree for high-order conditional entropy coding. In order to make the high-speed conditional entropy coder feasible, we introduce several key innovations in the areas of complexity reduction and hardware architecture. For complexity reduction, we develop two techniques: code table reduction and nonlinear quantization of conditioning pixels. For hardware architecture, we propose a pattern-matching technique for fast conditioning state extraction and a multistage pipelined structure to handle the case of a large number of conditioning pixels. Using the complexity reduction techniques and the hardware structures, we demonstrate that It is possible to implement practical high-order conditional entropy codecs using current low-cost very large-scale Integration (VLSI) technology.

关键词： Hardware Entropy coding Huffman coding Probability Statistics Sun Information theory Data compression image coding Data mining

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C-LIENet: A Multi-Context Low-Light image Enhancement Network

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IEEE ACCESS 2021年 9卷 31053-31064页

作者： Ravirathinam, Praveen Goel, Divyam Ranjani, J. Jennifer Birla Inst Technol & Sci Dept Comp Sci & Informat Syst Pilani 333031 Rajasthan India

Enhancement of low-light images is a challenging task due to the impact of low brightness, low contrast, and high noise. The inability to collect natural labeled data intensifies this problem further. Many researchers have attempted to solve this problem using learning-based approaches;however, most models ignore the impact of noise in low-lit images. In this paper, an encoder-decoder architecture, made up of separable convolution layers that solve the issues encountered in low-light image enhancement, is proposed. The architecture is trained end-to-end on a custom low-light image dataset (LID), comprising both clean and noisy images. We introduce a unique multi-context feature extraction module (MC-FEM) where the input first passes through a feature pyramid of dilated separable convolutions for hierarchical-context feature extraction followed by separable convolutions for feature compression. The model is optimized using a novel three-part loss function that focuses on high-level contextual features, structural similarity, and patch-wise local information. We conducted several ablation studies to determine the optimal model for low-light image enhancement under noisy and noiseless conditions. We have used performance metrics like peak-signal-to-noise ratio, structural similarity index matrix, visual information fidelity, and average brightness to demonstrate the superiority of the proposed work against the state-of-the-art algorithms. Qualitative results presented in this paper prove the strength and suitability of our model for real-time applications.

关键词： Feature extraction Convolution image enhancement Noise measurement Lighting image coding Computer architecture Encoder-decoder architecture separable convolution dilated convolution ASPP perceptual loss low-light image enhancement

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Application of detector precision characteristics and histogram packing for compression of biological fluorescence micrographs

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2012年第2期108卷 511-523页

作者： Bernas, Tytus Starosolski, Roman Robinson, J. Paul Rajwa, Bartlomiej Silesian Tech Univ Inst Comp Sci PL-44100 Gliwice Poland Purdue Univ Cytometry Labs W Lafayette IN 47907 USA RCSI Dept Physiol & Med Phys Dublin 2 Ireland Jagiellonian Univ Dept Biochem Biophys & Biotechnol PL-30387 Krakow Poland

Modern applications of biological microscopy such as high-content screening (HCS), 4D imaging, and multispectral imaging may involve collection of thousands of images in every experiment making efficient image-compression techniques necessary. Reversible compression algorithms, when used with biological micrographs, provide only a moderate compression ratio, while irreversible techniques obtain better ratios at the cost of removing some information from images and introducing artifacts. We construct a model of noise, which is a function of signal in the imaging system. In the next step insignificant intensity levels are discarded using intensity binning. The resultant images, characterized by sparse intensity histograms, are coded reversibly. We evaluate compression efficiency of combined reversible coding and intensity depth-reduction using single-channel 12-bit light micrographs of several subcellular structures. We apply local and global measures of intensity distribution to estimate maximum distortions introduced by the proposed algorithm. We demonstrate that the algorithm provides efficient compression and does not introduce significant changes to biological micrographs. The algorithm preserves information content of these images and therefore offers better fidelity than standard irreversible compression method JPEG2000. (c) 2011 Elsevier Ireland Ltd. All rights reserved.

关键词： Microscope imaging Intensity resolution Histogram packing image compression image coding

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SUBBAND coding SYSTEMS INCORPORATING QUANTIZER MODELS

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IEEE TRANSACTIONS ON image PROCESSING 1995年第5期4卷 543-553页

作者： KOVACEVIC, J Signal Processing Research Department AT and T Bell Laboratories Inc. Murray Hill NJ USA

A new method for dealing with the effects of quantization in a subband system is proposed, It uses the ''gain plus additive noise'' linear model for the Lloyd-Max quantizer, Based on this, it is demonstrated how, by an appropriate choice of synthesis filters, one can cancel all signal-dependent errors at the output of the system, The only remaining error is random in nature and not correlated with the input signal, We therefore have a tradeoff between the error being only random or having signal-dependent components as well (since the error variances in both cases are comparable), As a result of having only a random error, it is possible to reduce this error using, for example, a noise removal technique, The result is then extended to the case where the input is a multidimensional signal, and arbitrary sampling lattices are used, as well as to the QMF (alias cancellation) case, To demonstrate the validity of the proposed approach, two types of experiments on images are carried out: In a toy example, it is shown that using noise removal could be beneficial, For a more realistic coding scheme, however, it is demonstrated that even in the case when the model is no longer valid (when some of the subbands are discarded), the output error is still much less correlated with the input signal as opposed to the commonly used subband system, while visually, the reconstructed images look very similar.

关键词： Noise cancellation Quantization Additive noise Signal synthesis Filters Noise reduction Multidimensional systems image sampling Lattices image coding

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Advancing Copy-Move Manipulation Detection in Complex image Scenarios Through Multiscale Detector

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IEEE ACCESS 2024年 12卷 64736-64753页

作者： Diwan, Anjali Mahadeva, Rajesh Gupta, Vinay Marwadi Univ Dept CE AI Rajkot 360003 Gujarat India Khalifa Univ Dept Phys Abu Dhabi U Arab Emirates

This research presents a new approach for identifying instances of copy-move forgeries in digital images by utilizing the Multiscale Detector a Neural Network-based method, which serves as an image key-point detector and descriptor. The act of copy-move manipulation involves the replication and subsequent insertion of a specific segment of an image, intending to modify the overall content of the image. The approach we utilize leverages the sophisticated functionalities of Multiscale Detector, a framework that combines key-point detection with descriptor extraction, to accurately detect and localize instances of copy-move manipulation. The effectiveness of our approach is assessed on a range of copy-move forgeries, encompassing instances that have undergone post-processing and geometric transformations. The experimental findings illustrate the resilience of our approach in identifying instances of manipulations over a diverse range of textured images and various alteration approaches. Furthermore, our approach demonstrates strong performance even when subjected to supplementary processing procedures such as brightness modification, color reduction, contrast adjustment, and blurring. Our suggested method has greater performance when compared to the existing manipulation detection approach, as demonstrated through a comparative analysis. In addition, the algorithm we have developed has high computing efficiency, allowing for real-time detection of forgeries. The methodology employed in this study, which builds upon the Multiscale Detector framework, offers a highly effective approach to the detection of copy-move manipulations in digital images.

关键词： Forgery Feature extraction Digital images image coding image quality image color analysis Neural networks Computer vision Detection algorithms Copy-move forgery multiscale detector neural network computer vision image forensics forgery detection

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Effects of image compression on face image manipulation detection: A case study on facial retouching

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IET BIOMETRICS 2021年第3期10卷 342-355页

作者： Rathgeb, Christian Bernardo, Kevin Haryanto, Nathania E. Busch, Christoph Hsch Darmstadt Da Sec Biometr & Internet Secur Res Grp Darmstadt Germany

Numerous methods have been introduced to reliably detect digital face image manipulations in the past. Of late, the generalisability of these schemes has been questioned in particular with respect to image post-processing. image compression represents a post-processing which is frequently applied in diverse biometric application scenarios. Severe compression might erase digital traces of face image manipulation and hence hamper a reliable detection thereof. In this work, the effects of image compression on the face image manipulation detection are analysed. In particular, a case study on facial retouching detection under the influence of image compression is presented. To this end, ICAO-compliant subsets of two public face databases are used to automatically create a database containing more than 9000 retouched reference images together with unconstrained probe images. Subsequently, reference images are compressed applying JPEG and JPEG 2000 at compression levels recommended for face image storage in electronic travel documents. Novel detection algorithms utilising texture descriptors and deep face representations are proposed and evaluated in a single image and differential scenario. Results obtained from challenging cross-database experiments in which the analysed retouching technique is unknown during training yield interesting findings: (1) most competitive detection performance is achieved for differential scenarios employing deep face representations;(2) image compression severely impacts the performance of face image manipulation detection schemes based on texture descriptors while methods utilising deep face representations are found to be highly robust;(3) in some cases, the application of image compression might as well improve detection performance.

关键词： biometrics (access control) data compression face recognition feature extraction image coding image texture

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DEVELOPMENT OF A SHAPE-FROM-SHADING TECHNIQUE FOR THE EXTRACTION OF TOPOGRAPHIC MODELS FROM INDIVIDUAL SPACEBORNE SAR imageS

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1990年第4期28卷 654-661页

作者： GUINDON, B Canada Center for Remote Sensing Ottawa ON K1A OY7 2464 Shef- field Road Canada

A fundamental aspect of the extraction of topographic information from single steep-viewing SAR scenes is addressed, namely, the relationship between image grey level and terrain orientation. image radiometry of steep-looking radars is seen to be most sensitive to the range-directed component of terrain slope. This observation is critical since “classical” shape-from-shading methodologies are based on the implicit assumption that observed reflectance is indicative of the full three-dimensional (3D) surface orientation defined by both slope and aspect. A new shape-from-shading technique is proposed in which radiometry is used to generate independent elevation profiles for each image range line. Experiments have been carried out using two Seasat subscenes of mountainous terrain. Evaluations of topographic accuracy have been accomplished through a comparison of elevation profiles inferred from the imagery and corresponding transect information extracted from available 1: 50 000 scale maps. © 1990 IEEE

关键词： Lakes Radiometry Layout Surface topography Reflectivity Synthetic aperture radar Remote sensing Speckle Dynamic range image coding

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Adaptive Geometry Partition for Point Cloud Compression

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2021年第12期31卷 4561-4574页

作者： Zhang, Xiang Gao, Wen Tencent Amer Media Lab Palo Alto CA 94306 USA

Octree (OT) geometry partitioning has been acknowledged as an efficient representation in state-of-the-art point cloud compression (PCC) schemes. In this work, an adaptive geometry partition and coding scheme is proposed to improve the OT based coding framework. First, quad-tree (QT) and binary-tree (BT) partitions are introduced as alternative geometry partition modes for the first time under the context of OT-based point cloud compression. The adaptive geometry partition scheme enables flexible three-dimensional (3D) space representations and higher coding efficiency. However, exhaustive searching for the optimal partition from all possible combinations of OT, QT and BT is impractical because the entire search space could be huge. Therefore, two hyper-parameters are introduced to specify the conditions on which QT and BT partitions will be applied. Once the two parameters are determined, the partition mode can be derived according to the geometry shape of current coding node. To investigate the impact of different partition combinations on the coding gains, we conduct thorough mathematical and experimental analyses. Based on the analyses, an adaptive parameter selection scheme is presented to optimize the coding efficiency adaptively, where multi-resolution features are extracted from the partition pyramid and a decision tree model is trained for the optimal hyper-parameters. The proposed adaptive geometry partition scheme has shown significant coding gains, and it has been adopted in the state-of-the-art MPEG Geometry based PCC (G-PCC) standard. For the sparser point clouds, the bit savings are up to 10.8% and 3.5% for lossy and lossless geometry coding without significant complexity increment.

关键词： Encoding Geometry Three-dimensional displays Standards Transform coding Video coding image coding Point cloud compression geometry coding octree partition quad-tree partition binary-tree partition

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TERA: Screen-to-Camera image Code With Transparency, Efficiency, Robustness and Adaptability

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IEEE TRANSACTIONS ON MULTIMEDIA 2022年 24卷 955-967页

作者： Fang, Han Chen, Dongdong Wang, Feng Ma, Zehua Liu, Honggu Zhou, Wenbo Zhang, Weiming Yu, Nenghai Univ Sci & Technol China CAS Key Lab Electromagnet Space Informat Hefei 230026 Peoples R China Microsoft Res Redmond WA 98052 USA

With the rapid development of digital devices, the issue of how to transmit information among different devices with multimedia carriers has drawn much attention from the research community. This paper focuses on the important user scenario of "screen-to-camera information transmission". Along this direction, image coding-based techniques have been shown to be the most popular and effective methods in the past decades. However, after careful study, we find that none of the existing methods can satisfy the four important properties simultaneously, i.e., high transparency, high embedding efficiency, strong transmission robustness and high adaptability to device types. This is mainly because these properties are contradictory with each other. In this paper, we thus propose a screen-to-camera image code dubbed "TERA" (transparency, efficiency, robustness and adaptability), which makes it possible to circumvent the contradiction among the above four properties for the first time. Generally, TERA adopts the color decomposition principle to ensure the visual quality and the superposition-based scheme to ensure embedding efficiency. BCH-coding-based information arrangement and a powerful attention-guided information decoding network are further designed to guarantee the robustness and adaptability. Through extensive experiments, the superiority and broad applications of our method are demonstrated.

关键词： Robustness Cameras Distortion Visualization image coding Decoding Two dimensional displays Adaptability attention-guided color decomposition efficiency robustness screen-to-camera image code transparency

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