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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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Grayscale image coding using optimal pixel grouping and adaptive multi-grouping division block truncation coding

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第13期81卷 17937-17958页

作者： Hu, Yu-Chen Liu, Jain-Shing Lo, Chun-Chi Wu, Chang-Ming Chen, Yu Providence Univ Dept Comp Sci & Informat Management 200Sec 7Taiwan Blvd Taichung 43301 Taiwan Providence Univ Dept Comp Sci & Informat Engn Taichung Taiwan Chung Yuan Christian Univ Dept Elect Engn Taoyuan 32023 Taiwan Fujian Univ Technol Sch Informat Sci & Engn Fuzhou 350118 Peoples R China

An efficient grayscale image coding scheme based on block truncation coding (BTC) is proposed. The optimal pixel grouping mechanism and the multi-grouping division process are employed in the proposed scheme. An entropy-based indicator generation mechanism is employed to generate the block indicators of different groups. In addition, an optional bit rate reduction mechanism for dynamic block division is designed. Simulation results verify that significant image quality gain is acquired by the proposed scheme compared to the state-of-art image coding methods based on BTC. Meanwhile, a lower bit rate is consumed by the proposed scheme.

关键词： Image coding block truncation coding Multi-grouping block truncation coding Optimal pixel grouping

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An Improved block truncation coding Using Rectangular Non-symmetry and Anti-packing Model 18th

An Improved Block Truncation Coding Using Rectangular Non-sy...

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18th International Conference on Intelligent Computing (ICIC)

作者： Zheng, Yunping Xu, Yuan Kuang, Jinjun Sarem, Mudar South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China Huazhong Univ Sci & Technol Sch Software Engn Wuhan Peoples R China Gen Org Remote Sensing Damascus Syria

ISBN: (纸本)9783031138706;9783031138690

block truncated coding (BTC) is an image compression algorithm with a simple coding process and a high coding speed, which can be used in the field of military communications with high real-time requirements. As the price of pursuing simplicity and high speed, the compression ratio and the quality of the decoded image are sacrificed to some extent. Although some strategies have been proposed to improve the compression ratio and the quality of the decoded images, the effect is not obvious. Inspired by the quadtree-based block truncation coding (QEDBTC) and the non-symmetry and anti-packing model (NAM), in this paper, we propose a novel rectangular NAM-based block truncation algorithm (RNAMEDBTC), which uses rectangular NAM strategy to divide the initial blocks into rectangular homogeneous blocks. The spatial frequency measurement (SFM) is used as a measurement parameter to subdivide the initial blocks. For each homogeneous block, we replace the high and low quantization values and the binary bitmaps in the traditional block truncation coding with the average value of the pixels in the block, thereby a great improvement of the compression rate of the algorithm is achieved. In order to further improve the compression rate, we have increased the area of the smaller homogeneous blocks, and thus reducing the number of homogeneous blocks. These expanded blocks are called non-homogeneous blocks. For each non-homogeneous block, we need to do error diffusion block truncation coding (EDBTC) processing. The experimental results in this paper show that without degrading the quality of the decoded image, the proposed algorithm improves the compression rate significantly by 158.3% and 30.8% higher than the traditional BTC and QEDBTC algorithms, respectively.

关键词： block truncation coding Non-symmetry and Anti-packing model SFM

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A dual-embedded tamper detection framework based on block truncation coding for intelligent multimedia systems

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INFORMATION SCIENCES 2023年 649卷

作者： Li, Mianjie Liu, Chihui Shan, Chun Song, Houbing Lv, Zhihan Guangdong Polytech Normal Univ Sch Elect & Informat Guangzhou 510665 Peoples R China Guangzhou Univ Cyberspace Inst Adv Technol Guangzhou 510006 Peoples R China Guangdong Artificial Intelligence & Digital Econ L Guangzhou 510005 Peoples R China Univ Maryland Baltimore Cty UMBC Dept Informat Syst Baltimore MD 21250 USA Uppsala Univ Fac Arts Dept Game Design Uppsala Sweden

The rich intelligent multimedia systems provide great convenience and efficiency. Unfortunately, it faces a series of security challenges and threats in developing and deploying multimedia ser-vices, such as tampering, hijacking, and adversarial attacks. Therefore, this paper proposes a dual -embedding framework based on block truncation coding to improve the security of intelligent multimedia systems. First, the signal is decomposed in frequency domain by using approximate translation invariance to obtain multi-layer frequency-domain parameters;then, this paper hides the encrypted data in two layers of low-frequency coefficients through fragile and robust embedding algorithms, respectively. In addition, in order to further improve the security per-formance, this paper adopts the method of block truncation coding to encrypt the embedded data. On the basis of performance analysis, the superiority of this method is illustrated by comparing with the existing methods.

关键词： Intelligent multimedia systems Approximate translation invariance Dual -embedding framework block truncation coding Tamper detection

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VLSI Design Based on block truncation coding for Real-Time Color Image Compression for IoT

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SENSORS 2023年第3期23卷 1573-1573页

作者： Chen, Shih-Lun Chou, He-Sheng Ke, Shih-Yao Chen, Chiung-An Chen, Tsung-Yi Chan, Mei-Ling Abu, Patricia Angela R. Wang, Liang-Hung Li, Kuo-Chen Chung Yuan Christian Univ Dept Elect Engn Taoyuan City 320317 Taiwan Ming Chi Univ Technol Dept Elect Engn New Taipei City Taiwan Jiaying Univ Sch Phys Educ Coll Meizhou 514000 Peoples R China Ateneo Manila Univ Dept Informat Syst & Comp Sci Quezon City 1108 Philippines Fuzhou Univ Coll Phys & Informat Engn Dept Microelect Fuzhou 350025 Peoples R China Chung Yuan Christian Univ Dept Informat Management Taoyuan City 320317 Taiwan

It has always been a major issue for a hospital to acquire real-time information about a patient in emergency situations. Because of this, this research presents a novel high-compression-ratio and real-time-process image compression very-large-scale integration (VLSI) design for image sensors in the Internet of Things (IoT). The design consists of a YEF transform, color sampling, block truncation coding (BTC), threshold optimization, sub-sampling, prediction, quantization, and Golomb-Rice coding. By using machine learning, different BTC parameters are trained to achieve the optimal solution given the parameters. Two optimal reconstruction values and bitmaps for each 4 x 4 block are achieved. An image is divided into 4 x 4 blocks by BTC for numerical conversion and removing inter-pixel redundancy. The sub-sampling, prediction, and quantization steps are performed to reduce redundant information. Finally, the value with a high probability will be coded using Golomb-Rice coding. The proposed algorithm has a higher compression ratio than traditional BTC-based image compression algorithms. Moreover, this research also proposes a real-time image compression chip design based on low-complexity and pipelined architecture by using TSMC 0.18 mu m CMOS technology. The operating frequency of the chip can achieve 100 MHz. The core area and the number of logic gates are 598,880 mu m(2) and 56.3 K, respectively. In addition, this design achieves 50 frames per second, which is suitable for real-time CMOS image sensor compression.

关键词： image sensor machine learning IoT block truncation coding bit map YEF color space color sampling image compression Golomb-Rice coding

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A self-recovery watermarking scheme based on block truncation coding and quantum chaos map

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第25-26期79卷 18695-18725页

作者： Hemida, Omer He, Hongjie Southwest Jiaotong Univ Sichuan Key Lab Signal & Informat Proc Chengdu Sichuan Peoples R China

To take into account the invisibility, recovery quality, detection ability, and security, a new digital image fragile watermarking method based on block truncation coding (BTC) and quantum chaos map is proposed. In this method generates the authentication watermark for each 4x4 block and generates the recovery watermark for each 2x2 block by block truncation coding. For each block, the block truncation coding is used to classify the image blocks into smooth blocks and rough blocks. For different blocks, recovery data can be generated by allocating fewer bits to the smooth blocks and more bits to the rough blocks to encoding the block content. Quantum chaos map is used to generate the block mapping sequence for embedding recovery watermark to improve the shortcoming of watermarking such as small keyspace and low security. The experimental results show that the proposed scheme improves the quality of watermarked and recovered images. Additionally, this approach achieves higher security than the existing methods, under different attacks, such as general tampering, collage attack, content-only, and a hybrid attack.

关键词： Fragile watermarking block truncation coding Quantum chaos Recovery performance

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block truncation coding based effective watermarking scheme for image authentication with recovery capability

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第4期78卷 4197-4215页

作者： Singh, Durgesh Singh, Sanjay K. Indian Inst Technol BHU Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India

Due to the advancement of photo-editing software, powerful computers and high resolution capturing devices, it has become tough to prevent the digital image from tampering. So, in these days just by looking a digital image we cannot say whether it is a genuine or not. This is why digital image authentication, as well as restoration, has become the essential issues, especially when it is utilized in medical science, evidence of court, and forensic science. This paper proposes an effective self-embedding fragile watermarking technique for the digital image authentication as well as recovery. The watermark is generated by quantization, and block truncation coding (BTC) of each 2 x 2 non-overlapping block and embedded in three least significant bits (LSBs) of the corresponding mapped block. The recovery bits are derived from most significant bits (MSBs) of the host image, and the authentication bits are derived from recovery bits, the spatial location of pixels and watermark keys. Even if tempering rate is 50%, the reconstruction of tampered image is achieved with high peak signal-to-noise ratio (PSNR) and normalized correlation coefficient (NCC). The experimental results demonstrate that the proposed scheme not only outperforms high-quality recovery fidelity but also negotiate the blocking artifacts additionally it improves the accuracy of tamper localization due to the use of very small size blocks.

关键词： Digital image watermarking Self-embedding watermarking block truncation coding Image authentication Image restoration

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Image Authentication Using block truncation coding in Lifting Wavelet Domain

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INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS 2022年第1期22卷 p1-14页

作者： Bhardwaj, Anuj Verma, Vivek Singh Gupta, Sandesh Jaypee Inst Informat Technol Dept Math Noida 201309 Uttar Pradesh India Ajay Kumar Garg Engn Coll Dept Informat Technol Ghaziabad 201009 Uttar Pradesh India CSJM Univ Univ Inst Engn & Technol Dept Comp Sci & Engn Kanpur 208024 Uttar Pradesh India

Image watermarking is one of the most accepted solutions protecting image authenticity. The method presented in this paper not only provides the desired outcome also efficient in terms of memory requirements and preserving image characteristics. This scheme effectively utilizes the concepts of block truncation coding (BTC) and lifting wavelet transform (LWT). The BTC method is applied to observe the binary watermark image corresponding to its gray-scale image. Whereas, the LWT is incorporated to transform the cover image from spatial coordinates to corresponding transform coordinates. In this, a quantization-based approach for watermark bit embedding is applied. And, the extraction of binary watermark data from the attacked watermarked image is based on adaptive thresholding. To show the effectiveness of the proposed scheme, the experiment over different benchmark images is performed. The experimental results and the comparison with state-of-the-art schemes depict not only the good imperceptibility but also high robustness against various attacks.

关键词： Robustness imperceptibility digital watermarking block truncation coding lifting wavelet transform

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A systematic survey on block truncation coding based data hiding techniques

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第22期78卷 32239-32259页

作者： Kumar, Rajeev Jung, Ki-Hyun Wookyung Informat Technol IT Res & Dev Ctr Daegu 41519 South Korea Kyungil Univ Dept Cyber Secur 50 Gamasil Gil Gyongsan 38428 Gyeongbuk South Korea

block truncation coding is one of the simplest encoding methods which require insignificant computing cost to compress images. Due to the vast demand on embedding data into compressed images with low computing cost, a number of data hiding methods to improve block truncation coding have been proposed to be suitable for the low power devices such as IoT devices, field-programmable gate array, and portable image signal processor. In this paper, block truncation coding based data hiding methods will be discussed and analyzed on two key metrics - data hiding capacity and image quality - as many researchers are focusing to increase the image quality along with data hiding capacity. Here, our aim is to provide guidance to interested researchers for their future works in the field of block truncation coding based data hiding techniques. Finally, future directions of research with some suggestions will be discussed.

关键词： Data hiding block truncation coding Information hiding BTC AMBTC Steganography

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

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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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