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5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Wang Xiaoyan Zhang Limin Yang Bo Li Rui Chai Pei State Grid Shandong Elect Power Construct Co Jinan Shandong Peoples R China

ISBN: (纸本)9781665423144

At present, massive amounts of image data have been generated at the power construction site. Due to the limitation of power communication transmission bandwidth, it is necessary to improve the low bit rate, high compression ratio, and anti-interference of the image, which is very necessary for on-site management personnel under the premise of ensuring efficient information transmission. Aiming at the above problems, this paper proposes an improved algorithm based on Set Partitioning in Hierarchical Trees (SPIHT). Firstly, the feature value of the image is extracted, and then the wavelet encoding is performed to obtain the compressed image. Compared with the traditional multi-level tree ensemble splitting algorithm, experimental data show that the image compressed by this algorithm has better visual effects and higher peak signal-to-noise ratio. Therefore, the method can effectively improve the transmission performance of the on-site image of the infrastructure construction, and ultimately improve the efficiency of the on-site inspection for violations.

关键词： image compression algorithm image transmission data intelligent analysis case analysis

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An image compression algorithm using reordered wavelet coefficients with compressive sensing

An image compression algorithm using reordered wavelet coeff...

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International Conference on image Processing Theory, Tools and Applications

作者： Mohamed Deriche Muhammad Ali Qureshi Azeddine Beghdadi King Fahd University of Petroleum and Minerals L2TI Institut Galilee Universite Paris 13

ISBN: (纸本)9781479986385

In this paper, we propose a new approach for image compression based on compressive sensing (CS). We introduce a new formulation of sparse vectors for rearranging multilevel 2-D Wavelet coefficients into a structured manner using parent-child relationships. We then use a Gaussian measurement matrix normalized with the weighted average Root Mean Squared (RMS) energies of different wavelet subbands. Compressed sampling is finally performed using this normalized measurement matrix. At the decoding stage, the image is reconstructed using a simple l_1-minimization technique. The proposed wavelet-based CS compression results in performance increase compared to other conventional CS-based techniques. Our experimental results show that the proposed algorithm outperforms existing approaches over different natural images.

关键词： Discrete wavelet transform Compressed sensing Adaptive sampling image quality compression Compressed sensing Resampling discrete wavelet transform image compression algorithm Wavelet coefficients image quality measurement matrix compression Parent Child Relations image compression Data compression

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Study of the Discrete Wavelet Transform Based on JPEG2000 image compression algorithm

Study of the Discrete Wavelet Transform Based on JPEG2000 Im...

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International Conference on Intelligent Materials and Mechatronics (IMM 2013)

作者： Cai, Jin Wang, Shuo Shenyang Aerosp Univ Coll Civil Aviat Shenyang 110136 Liaoning Peoples R China Shenyang Aerosp Univ Fac Aerosp Engn Shenyang 110136 Liaoning Peoples R China

ISBN: (纸本)9783037859353

JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store the image data continue to evolve. The size and bit depth collected for an image to increase the resolution and extend the dynamic range and color gamut. Discrete Wavelet transform based embedded image coding method is the basis of JPEG2000. image compression algorithm for the proper use and display of the image is a requirement for digital photography.

关键词： Discrete Wavelet Transform (DWT) JPEG2000 image compression algorithm

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An Efficient Lossless image compression algorithm for External Memory Bandwidth Saving

An Efficient Lossless Image Compression Algorithm for Extern...

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Data compression Conference (DCC)

作者： Haibing, Yin Hongqi, Hu China Jiliang Univ 258 Xueyuan St Hangzhou 310018 Zhejiang Peoples R China Shilan Microelectron Ltd 8 Huanggushan Rd Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781479938827

Huge SDRAM memory access bandwidth is the performance bottleneck for high definition video coding. Lossless image compression is efficient method to solve this problem. image pixels are compressed before writing into SDRAM and decompressed after reading out from SDRAM. This work proposes a hardware-oriented lossless image compression algorithm, supporting block and line random access patterns flexibly.

关键词： External Memory Bandwidth Saving SDRAM high definition video coding SDRAM lossless compression lossless image compression image compression algorithm readout external memory Writing

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image compression algorithms Based on Super-Resolution Reconstruction Technology

Image Compression Algorithms Based on Super-Resolution Recon...

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International Conference on image, Vision and Computing (ICIVC)

作者： Yaning Tan Juanjuan Cai Shengqian Zhang Wei Zhong Long Ye Key Laboratory of Media Audio and Video Communication University of China Ministry of Education Beijing China

ISBN: (纸本)9781728123264

In the era of intelligent media, we all need high quality image or video information. However, due to the limitation of bandwidth or storage resource, we usually use low bit rate coding technology for image compression. But the image distortion caused will bring in a visually inferior experience, and the actual information obtained is often not sufficient. Therefore, the super-resolution reconstructed image coding technology is researched to provide a higher dynamic bit rate variation range. Based on image super-resolution reconstruction, this paper proposes two targeted image compression coding frameworks. Firstly, we compress the DCT down-sampled image as the input of super-resolution reconstruction, and use image completion as the pretreatment process of image super-resolution reconstruction, which effectively improves the quality of reconstructed image at low bit rate and, hence improves the coding efficiency. Secondly, a new image compression technique is proposed here which is based on residual compensation and super-resolution reconstruction. In the encoder, the super-resolution reconstructed image is subtracted from the original image to obtain the residual image which is compressed. In the decoder, the residual image is decompressed and added to the reconstructed image to complete the decoding process which achieves flexible rate control.

关键词： image compression Super-resolution reconstruction Down-sampling Deep learning super-resolution Data compression image compression Bit rate images imagery (Psychotherapy) down-sampling residual image image image DISTORTION Reconstructive Surgical Procedures image compression algorithm image compression method video information image quality

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Development of Integrated Sensor System for Intelligent Transportation System 18

Development of Integrated Sensor System for Intelligent Tran...

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18th IEEE International Colloquium on Signal Processing and Applications (CSPA)

作者： Azares, John Emmanuel G. Centino, Mark Joshua A. Dela Cruz, Jennifer Nopia, John Paul A. Amado, Timothy M. Mapua Univ Sch Elect Elect & Comp Engn Manila Philippines

ISBN: (纸本)9781665485296

Traffic congestion has always been a major problem in the Philippines. This project study developed an integrated sensor system for intelligent transportation, which addressed the lack of automatic traffic monitoring systems to achieve traffic efficiency and safety. The researchers utilized different sensors in gathering data such as water level, temperature, and humidity within a certain area as well as a camera in capturing images and compared the three image compression algorithms, mainly the DCT (Discrete Cosine Transform), DWT (Discrete Wavelet Transform) and SVD (singular value decomposition) in terms of different parameters used in describing and identifying the best type of image compression to be applied prior to transmission to other different nodes. MSE (mean squared error) value, PSNR (Peak signal-to-noise ratio), Compress Ratio, and Process Time were the values of comparison in determining the best compression technique or algorithm for the gathered images. As a result, it was found that DCT characterized the best parameters for image compression. DCT produced the highest PSNR (52.41979dB), the lowest value for MSE (0.37247), and the lowest process time (0.16181s), while SVD was able to produce the most compressed image. This project also utilized solar renewable energy for the power management system, which enabled the system to run independently without any other external power source. This will be beneficial for the community to identify which roads can be used to optimize the mobility of the vehicles and maximize the use of renewable energy;hence will help reduce the traffic congestion issues in the country.

关键词： sensor system transportation DCT DWT solar energy image compression algorithm

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Study of the Discrete Wavelet Transform Based on JPEG2000 image compression algorithm

Study of the Discrete Wavelet Transform Based on JPEG2000 Im...

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2013 International Conference on Intelligent Materials and Mechatronics(IMM 2013)

作者： Jin Cai Shuo Wang College of Civil Aviation Shenyang Aerospace University Faculty of Aerospace Engineering Shenyang Aerospace University

关键词： Discrete Wavelet Transform(DWT) JPEG2000 image compression algorithm

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Three-dimensional separate descendant-based SPIHT algorithm for fast compression of high-resolution medical image sequences

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IET image PROCESSING 2017年第1期11卷 80-87页

作者： Song, Xiaoying Huang, Qijun Chang, Sheng He, Jin Wang, Hao Wuhan Univ Sch Phys & Technol Wuhan Hubei Peoples R China

To provide a fast compression algorithm for high-resolution medical image sequences, an efficient three-dimensional (3D) separate descendant-based (SBD) set partitioning in hierarchical trees (SPIHT) algorithm (3D SDB-SPIHT) is proposed in this study. To accelerate the transformation, 3D integer wavelet transform is used first. Based on an efficient spatial-temporal tree structure, which is designed for the transformed coefficients, the authors propose a fast coding scheme by separating the descendant set into offspring set and leaves set. The proposed algorithm has more selectivity in deciding the scanning and coding of the descendant sets and hence the coding time is accelerated. Experimental results demonstrate that 3D SDB-SPIHT compresses medical images faster compared with traditional 3D SPIHT and other variations of 3D SPIHT.

关键词： medical image processing image coding data compression image sequences trees (mathematics) wavelet transforms image scanners three-dimensional separate descendant based SPIRT algorithm high-resolution medical image sequence image compression algorithm 3D SBD set partitioning in hierarchical tree algorithm 3D integer wavelet transform spatial-temporal tree structure fast image coding scheme offspring set leaves set

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Quality Assessment of Deep-Learning-Based image compression 20

Quality Assessment of Deep-Learning-Based Image Compression

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20th IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Valenzise, Giuseppe Purica, Andrei Hulusic, Vedad Cagnazzo, Marco Univ Paris Sud Cent Supelec CNRS L2SUMR 8506 F-91192 Gif Sur Yvette France Telecom ParisTech LTCI F-75013 Paris France Bournemouth Univ Fac Sci & Technol Dept Creat Technol Bournemouth Dorset England

ISBN: (纸本)9781538660706

image compression standards rely on predic coding. transform coding, quantization and entropy coding, in order to achieve high compression performance. Very recently, deep generative models have been used to optimize or replace some of these operations, with very promising results. However. so far no systematic and independent study of the coding performance of these algorithms has been carried out. In this paper, for the first time, we conduct a subjective evaluation of two recent deep learning-based image compression algorithnts, comparing them to JPEG 2000 and to the recent BPG image codec based on HEVC Intra. We found that compression approaches based on deep auto -encoders can achieve coding performance higher than JPEG 2000, and sometimes as good as BPG. We also show experimentally that the PSNR metric to be avoided when evaluating the visual quality of deep -learning-based methods, as artifacts have different characteristics from those of DCT or wavelet -based codecs. In particular, images compressed at low biirate appear more natural than JPEG 2000 coded pictu according to a no -reference naturalness measure. Our study indicates that deep generative models are likely to bring huge innovation into the video coding arena in the coming years.

关键词： JPEG Data compression image compression Quality assessment image compression algorithm Entropy coding Independent study codecs subjective evaluation discrete cosine transforms DCT gene

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Lossless image compression In Cloud Computing 1

Lossless Image Compression In Cloud Computing

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1st International Conference on Technical Advancements in Computers and Communications (ICTACC)

作者： Nivedha, B. Priyadharshini, M. Thendral, E. Deenadayalan, T. KCG Coll Technol Dept Comp Sci & Engn Madras Tamil Nadu India

ISBN: (纸本)9781509047970

Huge numbers of images are produced today with advent of the 'big data' era. To store and transmit data traditional compression methods are no longer satisfying. In this paper, we face this challenge and to achieve a higher compression rate we are taking the advantage of the correlations existing between images. An image compression system that encodes each image by referencing its correlated images in the cloud. By comparing these features, we first extract features from an image and retrieve its similar image from the massive images in the cloud. Different methods of compressing point cloud data such as directly by converting it into 2D images or by using tree- based approaches have been explored from the previous studies. In this study, rather than compress point cloud data directly to compress the image in cloud data, by converting it lossless into range images, and then using various image compression algorithms to reduce the volume of the data.

关键词： compression methods longer satisfying reduce images lossless compression lossless image compression CLOUDS Clouds COMPRESSED imagery (Psychotherapy) image compression algorithm Cloud Computing Convert image two dimentional images Lossless compression ratio Reduce

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