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VLSI Implementation of Lossless ECG Compression Algorithm for Low Power Devices

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第12期67卷 3317-3321页

作者： Tsai, Tsung-Han Hussain, Muhammad Awais Natl Cent Univ Dept Elect Engn Taoyuan 320 Taiwan

This brief presents a VLSI implementation of an efficient lossless compression scheme for electrocardiogram (ECG) data encoding to save storage space and reduce transmission time. As compression algorithm is able to save storage space and reduce transmission time, this opportunity has been seized by implementing memory-less design while working at a high clock speed in VLSI. ECG compression algorithm comprises two parts: an adaptive linear prediction technique and content-adaptive golomb rice code. An efficient and low power VLSI implementation of compression algorithm has been presented. To improve the performance, the proposed VLSI design uses bit shifting operations as a replacement for the different arithmetic operations. VLSI implementation has been applied to the MIT-BIH arrhythmia database which is able to achieve a lossless bit compression rate of 2.77. Moreover, VLSI architecture contains 3.1 K gate count and core of the chip consumes 27.2 nW of power while working at 1 KHz frequency. The core area is 0.05 mm(2) in 90 nm CMOS process.

关键词： Electrocardiography Very large scale integration Encoding Hardware Compression algorithms Computer architecture Monitoring ECG compression golomb rice coding VLSI low power design adaptive linear prediction

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Modified Differential golomb Arithmetic Lossless Compression Algorithm for Smart Grid Applications

Modified Differential Golomb Arithmetic Lossless Compression...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

作者： Aleshinloye, Ahmed Bais, Abdul Univ Regina Elect Syst Engn Regina SK S4S 0A2 Canada

ISBN: (纸本)9781538645055

The advancement of the electric grid has led to tremendous growth in data generated from the installed sensors. Efficient storage and transmission of this data pose a challenge for the utilities. Thus, it is required to have a data compression technique to reduce the data size. There are state of the art compression algorithms that can be applied to reduce the amount of data for storage and transmission in the smart grid environment. Some of these algorithms exploit characteristics of the load profile data, where consecutive data samples have very small differences. However, performance of these algorithms deteriorate when there are frequent large differences. We propose a modification that improves compression performance when there are large value differences. The algorithm is evaluated on smart meter load profile data at different data resolution. We show that the proposed changes improve performance by 2 - 20% for different resolutions.

关键词： Smart grid exponential golomb coding binary adaptive arithmetic encoding golomb rice coding data granularity data resolution

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ROBUST IMAGE COMPRESSION ALGORITHM FOR VIDEO CAPSULE ENDOSCOPY: A REVIEW

ROBUST IMAGE COMPRESSION ALGORITHM FOR VIDEO CAPSULE ENDOSCO...

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International Conference on Intelligent Sustainable Systems (ICISS)

作者： Paul, Blessy Daise Babu, Caren Sahrdaya Coll Engn & Technol Trichur India

ISBN: (纸本)9781538677995

The goal of this work is to provide a brief review on the image compression algorithms in the wireless capsule endoscopy, which is efficient and simple. This paper also covers the review on each stage of the image compression algorithms and its efficiency. At the latter part of this paper, an ideal algorithm for the image compression with high compression ratio and good image reconstruction quality. The main complication associated with the wireless endoscopy system is the reduction in area and consumed power while preserving the acceptable reconstruction of video with high quality. Most of the existing algorithms are based on DCT algorithms which require more buffer space;thereby it increases the large area and large power for the computation. In this paper, the different data compressor based on DCT is presented. The ideal scheme is based on the subsampling of data. Special features and characteristics of endoscopic images are considered in the stage of algorithm development. The algorithm includes the compression technique differential pulse coded modulation (DPCM) which is lossless followed by simple, efficient and variable length encoding called golomb-rice coding. The proposed ideal image compressor is compatible with any image sensors which are low power and commercially available that outputs the pixels of the images in a raster scan manner. It will evict the need of the memory buffer and temporary storage needed in the transform based coding methods. Additional compression acquired by the introduction of the corner clipping algorithm to remove the distorted corners present in the endoscopic images. Compared to other algorithms aims at wireless capsule endoscopy, the proposed ideal algorithm is highly efficient with a high compression ratio as well as very high reconstruction peak signal-to-noise ratio.

关键词： DPCM DCT golomb rice coding PSNR CR subsampling

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DPCM BASED COMPRESSOR FOR CAPSULE ENDOSCOPIC VIDEOS

DPCM BASED COMPRESSOR FOR CAPSULE ENDOSCOPIC VIDEOS

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IEEE International Conference on Signal Processing and Communication (ICSPC)

作者： Babu, Caren Chandy, D. Abraham Karunya Univ Dept Elect & Commun Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781509067305

Wireless Capsule Endoscopy (WCE) is a recently established methodology that enables the capability to examine the interior of the human body with a non invasive procedure. The key challenge in capsule endoscopic system is developing a compressor with reduced area and power while capable of compressing this enormous amount of data. This paper focuses on developing a low complexity, low power compressor for video capsule endoscopic applications. Here the characteristics of endoscopic images are analyzed first and an algorithm is developed around these characteristics so that it better suits the application. Taking the advantage of limited color content of endoscopic image, the proposed algorithm converts RGB image into YUV color space. This is followed by DPCM and golomb rice coding and the image is converted to compressed bit stream. The reconstructed images are analysed, the proposed compressor performs strongly with an average compression rate of 77.238% and overall PSNR of 33.434dB. The low complexity and low power design of the system make it worth for hardware implementation inside the capsule.

关键词： Wireless Capsule Endoscopy Video compression Color space conversion DPCM golomb rice coding

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Efficient scheme for WCE image compression based on strategic chroma subsampling and encoding

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2022年第PartB期71卷 103184-103184页

作者： Babu, Caren Chandy, D. Abraham Christinal, Hepzibah A. Christ Coll Engn Dept Elect & Commun Engn Irinjalakuda India Karunya Inst Technol & Sci Dept Elect & Commun Engn Coimbatore India Karunya Inst Technol & Sci Dept Math Coimbatore India

The data generated in wireless capsule endoscopy during the examination of the gastrointestinal tract is huge and demands large storage and processing time. One of the essential components of the capsule is the compression module that needs to be low power and a low complexity one. This paper aims to bring significant improvement in pre-processing, chroma subsampling and encoding stages of image compression. Among various chrominance based color spaces, YEF being a best alternative for the RGB endoscopic image is analyzed in terms of statistical measures. New chroma subsampling patterns are tested, which has shown improved data reduction. In the encoder part, the combination of proposed predictive coder and the modified golomb rice coder generated better compressed bit stream. The cubic spline interpolation is the method used for image reconstruction during decompression. The endoscopic images from databases namely Gastrolab and WEO Clinical Endoscopy Atlas are utilized in the experimentation. The results show that the proposed near-lossless compression scheme performs better than the competing techniques in terms of compression rate, peak signal to noise ratio and structural similarity index.

关键词： Data compression Endoscopes Color space Subsampling Predictive coding golomb rice coding

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