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Adaptive and dynamic multi-grouping scheme for absolute moment block truncation coding

MULTIMEDIA TOOLS AND APPLICATIONS 2019年第7期78卷 7895-7909页

作者： Xiang, Zhaoyang Hu, Yu-Chen Yao, Heng Qin, Chuan Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn 516 Jungong Rd Shanghai 200093 Peoples R China Providence Univ Dept Comp Sci & Informat Management Taichung 43301 Taiwan

Image compression technique is widely used in multimedia signal processing. As a conventional lossy compression technique, block truncation coding (BTC) deserves further improvements to enhance its performance of compression. The improvements of BTC mainly focus on: 1) enhancing the quality of reconstructed image and 2) decreasing the bit rate. In this paper, an adaptive and dynamic multi-grouping scheme is proposed for the absolute moment block truncation coding (AMBTC), which is mainly based on an optimized grouping mechanism with the adaptive threshold setting according to the complexity of image blocks. Besides, the values of the reconstruction levels are replaced by their compressed difference values in order to decrease the bit rate. Experimental results demonstrate that the proposed scheme can enhance the compression performance of AMBTC effectively.

关键词： Image compression Lossy compression block truncation coding Multi-grouping

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VLSI implementation of an energy-efficient color image compressor using improved block truncation coding and enhanced Golomb-rice coding for wireless sensor networks

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JOURNAL OF SUPERCOMPUTING 2024年第17期80卷 24807-24834页

作者： Nirmala, R. Begum, S. Ariffa Selvanayagi, A. Ramya, P. Vivekanandha Coll Engn Women Autonomous ECE Tiruchengode India Kalasalingam Acad Res & Educ Sch Comp CSE Krishnan Koil Tamil Nadu India M Kumarasamy Coll Engn CSE Karur Tamil Nadu India Bannari Amman Inst Technol ECE Sathyamangalam Tamil Nadu India

The very large-scale integration implementation of a unique hardware-oriented image compression technique for wireless sensor networks (WSNs) is presented in this work. Networks of individually owned sensors spread out throughout an area that can detect, measure, and report changes in environmental variables are known as wireless sensor networks (WSNs). Color sampling, block truncation coding (BTC), threshold optimization, sub-sampling, estimation, quantization, and enhanced Golomb-rice coding (EGRC) are all included in the proposed design. A unique improved BTC with an enhanced Golomb-rice coding (IBTC-EGRC) framework has been proposed in this paper. IBTC training framework has been developed using the fuzzy decision-based approach to achieve representative levels and satisfy WSN requirements to accomplish the cost-effective and power-efficient features. Two ideal reconstruction values and bitmap files have been obtained for every block. IBTC divides images into variable block sizes for mathematical translation and inter-pixel redundancy removal. The subsampling, estimation, and quantization stages have minimized redundant data. Finally, EGRC has been used to code the value with the highest likelihood. An EGRC module decreases memory use and computation complexity. The EGRC technique reduces hardware resource utilization by removing the need for the context module, a crucial part of lossless image compressor designs and its memory. Proposed method, Golomb-rice parameter forecasting and managment module is used to preserve pixel connection and improved compression ratio. A UMC 180 nm CMOS technology has been used to implement the suggested framework. This design has 5.8k synthesized gate counts and a core area of 56,000 mu m2. 100 MHz and 3.01 mW were the operational frequency and energy consumption, respectively. The proposed method has a 9.37% reduction in gate count compared to the previous fuzzy BTC-based approach.

关键词： Image compressor VLSI Enhanced Golomb-rice coding WSN block truncation coding Fuzzy Energy efficiency Compression ratio Hardware utilization

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MODIFIED ALGORITHM FOR block truncation coding OF MONOCHROME IMAGES

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ELECTRONICS LETTERS 1985年第20期21卷 900-902页

作者： UDPIKAR, V RAINA, JP INDIAN INST TECHNOL DEPT ELECT ENGNFIBRE OPT COMMUN LABMADRAS 600036TAMIL NADUINDIA

block truncation coding (BTC) is a recent technique used in the coding of image data. In the letter a modified technique for BTC coding of image data is presented which is algorithmically simple and hence easy to implement. This new technique uses only the first-order statistical information as `block overhead??. The new algorithm is shown to be optimum in the mean-square sense for a particular class of BTC algorithms. The letter presents the results of using the new algorithm for a typical image and compares the performance with that of the earlier algorithm for the same image.

关键词： results data compression block truncation coding first-order statistical information algorithmically simple modified technique coding of image data mean-square errors image data compression monochrome images Optical information, image and video signal processing BTC video coding computerised picture processing performance Communications computing

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Optimisation of multi-level block truncation coding

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2001年第5期16卷 445-459页

作者： Chan, KW Chan, KL City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China

block truncation coding (BTC) is very attractive for real-time image coding at moderate bit-rate due to its low computation and storage demands. One major artefact of this image compression technique is edge raggedness. Modifications are mainly in two areas: bit-rate reduction and improvement of the quality of reconstructed image. Our investigation is in the latter area. In our integrated multi-level ETC scheme, the visual quality is substantially improved, the bit-rate is maintained the same as standard ETC and the computational demand is still kept low. We exploit various algorithms and derive new techniques to optimise the performance of multi-level ETC. Dynamic range tuning (DRT) is used to tackle 2-level ETC. Middle group settlement is used to carry out binary classification for tri-modal distribution. For 4-level ETC, an iterative DRT is derived. Based on our experience on 2- and 4-level BTCs, an optimised 3-level BTC is derived. Extensive testing has been carried out on 30 images. The resultant visual quality is nearly perfect and the PSNR may be boasted by up to 7 dB. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： image compression block truncation coding multi-level quantization

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MULTILEVEL block truncation coding USING A MINIMAX ERROR CRITERION FOR HIGH-FIDELITY COMPRESSION OF DIGITAL IMAGES

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IEEE TRANSACTIONS ON COMMUNICATIONS 1993年第8期41卷 1179-1191页

作者： WU, YY COLL, DC CARLETON UNIV DEPT SYST & COMP ENGN OTTAWA K1S 5B6 ONTARIO CANADA

This paper describes an encoding technique-multi-level block truncation coding-that preserves the spatial details in digital images while achieving a reasonable compression ratio. An adaptive quantizer-level allocation scheme is introduced, which minimizes the maximum quantization error in each block and substantially reduces the computational complexity in the allocation of optimal quantization levels. A 3.2:1 compression can be achieved by the multilevel block truncation coding itself. The truncated, or requantized, data are further compressed in a second pass using combined techniques of predictive coding, entropy coding, and vector quantization. The second pass compression can be lossless or lossy. The total compression ratios are about 4.1:1 for lossless second-pass compression, and 6.2:1 for lossy second-pass compression. The subjective results of the coding algorithm are quite satisfactory, with no perceived visual degradation.

关键词： compression ratio quantization level complexity classes compression Digital images block truncation coding error criterion Lossless multilayers Entropy coding Minimax Vector quantization high fidelity

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An FPGA implementation of a neural optimization of block truncation coding for image/video compression

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MICROPROCESSORS AND MICROSYSTEMS 2007年第8期31卷 477-486页

作者： Saif, Sherif Abbas, Hazent M. Nassar, Salwa M. Wahdan, Abdelmonem A. Mentor Graph Corp Cairo 11341 Egypt Elect Res Inst Comp & Syst Dept Giza Egypt Ain Shams Univ Dept Comp & Syst Engn Cairo Egypt

This paper presents a Field Programmable Gate Array (FPGA) implementation for image/video compression using an improved block truncation coding (BTC) image compression technique. The improvement is achieved by employing a Hopfield neural network (HNN) to calculate a cost function upon which a block is classified as either a high- or a low-detail block. Accordingly, different blocks are coded with different bit rates and thus resulting in better compression ratios. The paper formulates the utilization of HNN within the BTC algorithm in such a way that a viable FPGA implementation is produced. The implementation exploits the inherent parallelism of the BTC/HNN algorithm to provide efficient algorithm-to-architecture mapping. The Xilinx VirtexE BTC implementation has shown to provide a processing speed of about 1.113 x 10(6) of pixels per second with a compression ratio which varies between 1.25 and 2 bits/pixel, according to the image nature. (C) 2006 Elsevier B.V. All rights reserved.

关键词： field programmable gate arrays block truncation coding Hopfield neural networks image/video compression

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INTERPOLATIVE 3-LEVEL block truncation coding ALGORITHM (VOL 29, PG 1267, 1993)

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ELECTRONICS LETTERS 1993年第17期29卷 1591-1591页

作者： OSHRI, E SHELLY, N Signal Processing & Computing Division Elta Electronic Industries Ltd. Ashdod Israel Ben Gurion University of the Negev Beer-Sheva Israel

Zeng has described an interpolative two-level block truncation coding (BTC) image compression algorithm. The Letter extends the work of Zeng to a three-level interpolative BTC algorithm. Compared to Zeng, the new algo... 详细信息

关键词： interpolation data compression block truncation coding reconstructed images image coding Optical information, image and video signal processing Pattern recognition three-level interpolative BTC algorithm image compression image quality

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Edge detection using block truncation coding

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2003年第6期17卷 951-966页

作者： Hu, YC Chang, CC Providence Univ Dept Comp Sci & Informat Management Taichung 433 Taiwan Natl Chung Cheng Univ Dept Comp Sci & Informat Engn Chiayi 62107 Taiwan

In this paper, a new edge detection scheme based on block truncation coding (BTC) is proposed. As we know, the BTC is a simple and fast scheme for digital image compression. To detect an edge boundary using the BTC scheme, the bit plane information of each BTC-compressed block is exploited, and a simple block type classifier is introduced. The experimental results show that the proposed scheme clearly detects the edge boundaries of digital images while requiring very little computational complexity. Meanwhile, the edge detection process can be incorporated into all BTC variant schemes. In other words, the newly proposed scheme provides a good approach for the detection of edge boundaries using block truncation coding.

关键词： image processing edge detection image compression block truncation coding

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AN EFFICIENT HYBRID FEATURE FOR EDGE-PRESERVING BASED ON block truncation coding AND TREE-STRUCTURED VECTOR QUANTIZATION WITH EDGE ORIENTATION CLASSIFICATION OF BIT-PLANES

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2018年第3期14卷 929-946页

作者： Feng, Ya-Pei Lu, Zhe-Ming Zhejiang Univ Sch Aeronaut & Astronaut 38 Zheda Rd Hangzhou 310027 Zhejiang Peoples R China

In this paper, we propose a hybrid feature which merges block truncation coding (BTC) and Tree-Structured Vector Quantization (TSVQ) with classification of edge orientation bit-planes. BTC is known for its high quality of reconstructed images, much lower computational complexity and low compression ratios. Vector Quantization (VQ), on the other hand, results in very high compression ratios but with high complexity. To solve these problems, we propose an improved approach for feature extraction based on bit-plane classification according to the Edge Orientation of the Bit-Plane (EOBP) templates and combine it with TSVQ. As different areas of the image have different activities and contrasts, we encode the active blocks containing edges with BTC and EOBP templates, and encode the inactive blocks having low intensity variations between its pixels with the VQ. Different from the original BTC and VQ based feature extraction, we extract the edge orientation information by applying the EOBP classification on the bit-plane image blocks, as a result that we classify image blocks into 28 kinds with different edges. Simulation results show that our proposed method performs better in image compression and image retrieval.

关键词： block truncation coding VQ Feature extraction Edge Orientation of the Bit-Plane (EOBP) templates

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Hybrid block truncation coding

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IEEE SIGNAL PROCESSING LETTERS 1997年第12期4卷 328-330页

作者： Huang, CS Lin, YY Dept. of Electr. Eng. Nat. Central Univ. Chung-Li Taiwan Department of Electrical Engineering National Central University Chungli Taiwan

A hybrid block truncation coding (BTC) is presented in this work. In the hybrid ETC, a universal codebook using Ramming codes and a differential pulse code modulation (DPCM) are employed, respectively, to the bit plane and the side information of ETC to reduce coding rate. Simulation results reveal that the performance of the proposed algorithm is only slightly worse than that of the hybrid ETC using vector quantization (VQ) techniques, but with much lower computational or hardware complexity.

关键词： block truncation coding differential pulse code modulation Hamming codes vector quantization

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