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6th IEEE International Symposium on Signal Processing and Information Technology

作者： Zhou, Lele Zahir, Saif Univ Northern British Columbia Dept Comp Sci 3333 Univ Way Prince George BC V2N 4Z9 Canada

ISBN: (纸本)9780780397538

chain coding is widely used in a variety of image processing applications. In this paper, we present a new chain coding scheme: context-based relative-directional chain coding (CRCC). It applies a novel context modeling with adaptive arithmetic coding to encode contour images. The proposed context modeling is based on the relative-directional chain representation. It provides a favorable conditional probability for the next encoding pixel so that the arithmetic coding is efficiently performed. The experimental results shows that the CRCC coding scheme overall outperforms the chain coding (CC), Differential chain coding (DCC) and Differential chain coding Mode-8 (DCC-8). More importantly, the proposed CRCC coding scheme completely avoids the cost in computation of eight-directional chain codes and its associated sequence of differences.

关键词： chain coding arithmetic coding contour representation data compression

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CC-SMC: chain coding-based segmentation map lossless compression

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2024年 103卷

作者： Yang, Runyu Liu, Dong Wu, Feng Gao, Wen Univ Sci & Technol China MOE Key Lab Brain Inspired Intelligent Percept & C Hefei 230027 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China Peking Univ Beijing 100871 Peoples R China

A segmentation map, either static or dynamic, refers to a two-dimensional picture that may vary with time and indicates the segmentation label per pixel. Both the semantic map and the occupancy map in video-based point cloud compression (V-PCC) belong to the segmentation map we referred to. The semantic map can work for many machine vision tasks like tracking and has been used as a layer of image representation in some image compression methods. The occupancy map constitutes a part of the point cloud coding bitstream. Since segmentation maps are widely used, how to efficiently compress them is of interest. We propose a segmentation map lossless compression scheme namely CC-SMC, exploiting the nature of segmentation maps that usually contain limited colors and sharp edges. Specifically, we design a chain coding-based scheme combined with quadtree-based block partitioning. For intraframe coding, one block is partitioned recursively with a quadtree structure, until the block contains only one color, is smaller than a threshold, or satisfies the defined chain coding condition. We revise the three-orthogonal chain coding method to incorporate contextual information and design effective intraframe prediction methods. For interframe coding, one block may find a reference block;the chain difference between the current and the reference blocks is coded. We implement the proposed scheme and test it on several different kinds of segmentation maps. Compared with advanced lossless image compression techniques, our proposed scheme obtains more than 10% bits reduction as well as more than 20% decoding time-saving. The code is available at https://***/Yang-Runyu/CC-SMC.

关键词： chain coding Lossless compression Occupancy map Quadtree-based block partitioning Segmentation map Semantic map

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Enhanced Contour chain-coding and Topological Hierarchy Analysis in a Single-Pass Raster Scan

Enhanced Contour Chain-Coding and Topological Hierarchy Anal...

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35th International Conference on Telecommunications and Signal Processing (TSP)

作者： Scheffler, Marco Greiner, Thomas Pforzheim Univ MERSES Ctr Appl Res Pforzheim Germany

ISBN: (纸本)9781467311182

In this paper we present an enhancement of Cederberg's raster-scan approach for generating chain-encoded representations of contours of segmented regions and their inherent topological hierarchy tree within a binary image. The presented algorithm uses a 3 x 3 neighborhood window to build chain-code of all possible contour pixel arrangements of objects and holes within objects in a single pass through the image. The amount of template comparisons for each pixel window has been drastically reduced by taking basic interdependencies between a line-wise scanning beam and borders of binary objects into account. Furthermore, the complete topological hierarchy tree is established by inferring the global surroundness relations among the region borders from the previous obtained local information. With these main characteristics, the algorithm is well suited for efficient parallel processing implementations in streaming applications (e.g. in FPGAs) in that it avoids unpredictable memory accesses to a video frame buffer as can be found with the border following technique. Moreover - on the basis of the hierarchy tree - an effective pre-selection of contours can be established in that only objects or holes down to a defined child-level will be further processed, enabling significant bandwidth-savings for subsequent storage or transmission purposes.

关键词： Binary image compression boundary extraction chain coding contours topological analysis trees

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Contour chain-coding and Topological Hierarchy Analysis in a 2x3 Window Single-Pass Raster Scan

Contour Chain-Coding and Topological Hierarchy Analysis in a...

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36th International Conference on Telecommunications and Signal Processing (TSP)

作者： Scheffler, Marco Schumacher, Frank Greiner, Thomas Pforzheim Univ MERSES Ctr Appl Res Pforzheim Germany

ISBN: (纸本)9781479904020;9781479904037

This paper presents a fast and effective method for generating chain-encoded representations of arbitrary contours of connected regions in a binary image. Furthermore, an optional method is presented allowing the additional concurrent extraction of the topological hierarchy tree within the image. Both parts of the algorithm are executed by means of a single raster scan with a 2x3 neighborhood convolution window. This not only allows the reduction of the pixel buffer to a single image line, it furthermore enables fast neighborhood evaluation by means of a moderately sized look-up-table with 64 entries, to be directly addressed by the six pixel in window focus. With these main characteristics, the algorithm is well suited for efficient parallel processing implementations in streaming applications.

关键词： binary image coding boundary extraction chain coding topological analysis trees

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Learned Image Compression With Efficient Cross-Platform Entropy coding

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2025年第1期15卷 72-82页

作者： Yang, Runyu Liu, Dong Wu, Feng Gao, Wen Univ Sci & Technol China Key Lab Brain Inspired Intelligent Percept & Cogni MOE Hefei 230027 Peoples R China Peking Univ Sch Comp Sci Beijing 100871 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China

Learned image compression has shown remarkable compression efficiency gain over the traditional image compression solutions, which is partially attributed to the learned entropy models and the adopted entropy coding engine. However, the inference of the entropy models and the sequential nature of the entropy coding both incur high time complexity. Meanwhile, the neural network-based entropy models usually involve floating-point computations, which incur inconsistent probability estimation and decoding failure in different platforms. We address these limitations by introducing an efficient and cross-platform entropy coding method, chain coding-based latent compression (CC-LC), into learned image compression. First, we leverage the classic chain coding and carefully design a block-based entropy coding procedure, significantly reducing the number of coding symbols and thus the coding time. Second, since CC-LC is not based on neural networks, we propose a rate estimation network as a surrogate of CC-LC during the end-to-end training. Third, we alternately train the analysis/synthesis networks and the rate estimation network for the rate-distortion optimization, making the learned latent fit CC-LC. Experimental results show that our method achieves much lower time complexity than the other learned image compression methods, ensures cross-platform consistency, and has comparable compression efficiency with BPG. Our code and models are publicly available at https://***/Yang-Runyu/CC-LC.

关键词： Image coding Estimation Entropy coding Entropy Computational modeling Training Symbols Transforms Circuits and systems Time complexity Block-based coding chain coding cross-platform consistency entropy coding learned image compression

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chain Code-Based Occupancy Map coding for Video-Based Point Cloud Compression

Chain Code-Based Occupancy Map Coding for Video-Based Point ...

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IEEE International Conference on Visual Communications and Image Processing (VCIP)

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

ISBN: (纸本)9781728180687

In video-based point cloud compression (V-PCC), occupancy map video is utilized to indicate whether a 2-D pixel corresponds to a valid 3-D point or not. In the current design of V-PCC, the occupancy map video is directly compressed losslessly with High Efficiency Video coding (HEVC). However, the coding tools in HEVC are specifically designed for natural images, thus unsuitable for the occupancy map. In this paper, we present a novel quadtree-based scheme for lossless occupancy map coding. In this scheme, the occupancy map is firstly divided into several coding tree units (CTUs). Then, the CTU is divided into coding units (CUs) recursively using a quadtree. The quadtree partition is terminated when one of the three conditions is satisfied. Firstly, all the pixels have the same value. Secondly, the pixels in the CU only have two kinds of values and they can be separated by a continuous edge whose endpoints lie on the side of the CU. The continuous edge is then coded using chain code. Thirdly, the CU reaches the minimum size. This scheme simplifies the design of block partitioning in HEVC and designs simpler yet more effective coding tools. Experimental results show significant reduction of bit-rate and complexity compared with the occupancy map coding scheme in V-PCC. In addition, this scheme is also very efficient to compress the semantic map.

关键词： arithmetic coding chain coding occupancy map quadtree-based partition semantic map video-based point cloud compression

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Generalized predictive binary shape coding using polygon approximation

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2000年第7-8期15卷 643-663页

作者： Kim, JI Bovik, AC Evans, BL Univ Texas Dept Elect & Comp Engn Lab Image & Video Engn Austin TX 78712 USA Daewoo Elect Seoul South Korea

This paper introduces a new binary shape coding technique called generalized predictive shape coding (GPSC) to encode the boundary of a visual object compactly by using a vertex-based approach. GPSC consists of a contour pixel matching algorithm and a motion-compliant contour coding algorithm. The contour pixel matching algorithm utilizes the knowledge of previously decoded contours by using a uniform translational model for silhouette motion, and generalizes polygon approximation for lossless and lossy motion estimation by adjusting a tolerance parameter d(max). To represent motion-compliant regions with minimum information in the transmitted bitstream, we develop a reference index-based coding scheme to represent the 2D positions of the matched segments using 1D reference contour indices. Finally, we encode the mismatched segments by sending residual polygons until the distortion is less than d(max). While GPSC realizes polygon approximation exactly at every encoding stage, we can guarantee quality of service because the peak distortion is no greater than d(max), and we improve coding efficiency as long as a silhouette complies with the model. The tolerance parameter d(max) can be assigned to each contour to smooth the transmitted data rate, which is especially useful for constant bandwidth channels. Compared with non-predictive approaches, simulation using MPEG-4 sequences demonstrates that GPSC not only improves objective gain but also enhances visual quality based on MPEG-4 subjective tests. The significance of GPSC is that it provides a generic framework for seamlessly extending conventional vertex coding schemes into the temporal domain yet it retains the advantages of existing polygon-based algorithms for visual content description while furnishing better geometric compression. (C) 2000 Elsevier Science B.V, All rights reserved.

关键词： video coding chain coding contour coding contour motion estimation contour pixel matching contour representation predictive shape coding vertex coding

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Efficient and lossless compression of raster maps

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SIGNAL IMAGE AND VIDEO PROCESSING 2015年第1期9卷 133-145页

作者： Mao, Qingzhou Zhou, Baoding Zou, Qin Li, Qingquan Wuhan Univ State Key Lab Informat Engn Surveying Wuhan 430079 Peoples R China Wuhan Univ Sch Comp Sci Wuhan 430072 Peoples R China

In this paper, a block-line-separated encoding approach (BLiSE) is proposed for efficient and lossless compression of raster maps. Firstly, BLiSE separates a raster map into blocks and lines through a raster-map-decomposition algorithm. For each block, BLiSE uses a flag encoding to record the location and color information, and a 4-direction Freeman coding to encode the block boundary. For each line, BLiSE directly applies the 8-direction Freeman coding. With this separate-encoding strategy, BLiSE is highly suitable for compression of navigation maps. We evaluate BLiSE on a navigation-map dataset containing 100 raster maps and compare it with three traditional approaches, which are GIF, PNG and JP2000-LS. The results indicate an average compression ratio of 82.83 of the proposed BLiSE, which is much higher than that of several competing approaches.

关键词： Raster map Lossless compression Run-length encoding chain coding Mathematical morphology

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Mirror symmetry detection in curves represented by means of the Slope chain Code

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PATTERN RECOGNITION 2019年 87卷 67-79页

作者： Alvarado-Gonzalez, Montserrat Aguilar, Wendy Garduno, Edgar Velarde, Carlos Bribiesca, Ernesto Medina-Banuelos, Veronica Univ Autonoma Metropolitana Cuajimalpa Dept Appl Math & Syst Mexico City 05348 DF Mexico Univ Nacl Autonoma Mexico Inst Invest Matemat Aplicadas & Sistemas Dept Comp Sci Mexico City 04510 DF Mexico Univ Autonoma Metropolitana Iztapalapa Dept Elect Engn Neuroimaging Lab Mexico City 09340 DF Mexico

Symmetry is an important feature in natural and man-made objects;particularly, mirror symmetry is a relevant task in fields such as computer vision and pattern recognition. In the current work, we propose a new method to characterize mirror-symmetry in open and closed curves represented by means of the Slope chain Code. This representation is invariant under scale, rotation, and translation, highly desirable properties for object recognition applications. The proposed method detects symmetries through simple inversion, concatenation and reflection operations on the chains, thus allowing the classification of symmetrical and asymmetrical contours. It also introduces a measure to quantify the degree of symmetry in quasi-mirror-symmetrical objects. Furthermore, it allows the identification of multiple symmetry axes and their location. Results show high performances in symmetrical/asymmetrical classification (0.9 recall, 0.9 accuracy, 0.97 precision) and axes' detection (0.8 recall, 0.84 accuracy, 0.99 precision). Compared to other methods, the proposed algorithm provides properties such as: global, local, and multiple axes' detection, as well as the capability to classify symmetrical objects, which makes it adequate for several practical applications, like the three exemplified in the paper. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Symmetry detection Slope chain Code chain coding 2D curves

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A lossy/lossless compression method for printed typeset bi-level text images based on improved pattern matching

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INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION 2009年第4期11卷 159-182页

作者： Grailu, Hadi Lotfizad, Mojtaba Sadoghi-Yazdi, Hadi Tarbiat Modares Univ Dept Engn Tehran Iran Tarbiat Moallem Univ Sabzevar Dept Engn Sabzavar Iran Ferdowsi Univ Mashad Dept Comp Mashhad Iran

Pattern matching is the most widely used technique for the compression of printed bi-level text images. In some printed scripts, letters normally attach to each other, or some letters have a simple relation to each other, or there may be undesired touching characters. Detecting such situations and exploiting them to reduce the library size, has a rather great effect on the compression ratio. In this paper, a lossy/lossless compression method for printed typeset bi-level text images is proposed for archiving purposes. For this, three techniques are proposed. First, the number of library prototypes is reduced by detecting and exploiting the mentioned situations. Second, a new effective encoding scheme is proposed for patterns and numbers. Third, three levels are proposed for lossy compression. Experimental results show that the proposed method works better, as high as 1.4-3.3 times in lossy case and 1.2-2.7 times in lossless case at 300 dpi, than the best existing compression methods or standards.

关键词： Pattern encoding Library size reduction chain coding Attaching characters Pattern matching Binary text image compression

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