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检索条件"任意字段=4th Conference on Mathematics of Image and Data Coding, Compression, and Encryption"

共 249 条记录，以下是61-70 订阅

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Compressed vs. uncompressed domain video watermarking

Compressed <i>vs</i>. uncompressed domain video watermarking

引用

conference on mathematics of data/image Pattern Recongnition, compression, coding, and encryption X, with Applications

作者： Duta, S. Mitrea, M. Preteux, F. GET INT ARTEMIS Dept Evry France

ISBN: (纸本)9780819468482

When considering the multimedia production chain from the content creation to the end-user consumption, watermarking provides a well defined functionality: property right identification and copy-maker tracking. However, its place within this chain is not yet clearly stated. the present paper describes an objective study aiming at establishing the functional peculiarities in the cases when watermarking follows compression. First, some general limits concerning the transparency, robustness and capacity in compressed (WEG-4 AVC) domain watermarking are identified. then, these results are discussed and compared to the uncompressed domain watermarking case. the experiments were carried out on a video corpus of 5 video sequences, each of them of 35000 frames (about 25 minutes each), coded at 256kbit/s.

关键词： MPEG-4 AVC video watermarking transparency robustness capacity

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OPTICAL AND ELECTROOPTICAL ARCHITECTURES FOR thE compression and encryption OF DISCRETE SIGNALS AND imageRY .3. OPTICAL COMPUTATION OVER COMPRESSED data 4

OPTICAL AND ELECTROOPTICAL ARCHITECTURES FOR THE COMPRESSION...

引用

4th conference on Hybrid image and Signal Processing

作者： SCHMALZ, MS UNIV FLORIDA DEPT COMP & INFORMAT SCIGAINESVILLEFL 32611

ISBN: (纸本)0819415421

Due to a reduced space requirement, the output of compressive transformations can generally be processed with fewer operations than are required to process uncompressed data. Since 1992, we have published theory that unifies the processing compressed and/or encrypted imagery, and have demonstrated significant computational speedup in the case of compressive processing, In this paper, the third of a series, we extend our previously reported work in optical processor design based on image algebra to include the design of optical processors that compute over compressed data. Parts 1 and 2 describe optical architectures that are designed to produce compressed or encrypted imagery.

关键词： image processing image compression Spatial light modulators Computer programming Computer architecture image resolution data processing Electro optics image encryption Sensors

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An Unsupervised Learning Approach for Visual data compression with Chaotic encryption 4

An Unsupervised Learning Approach for Visual Data Compressio...

引用

4th International conference on Electrical, Computer and Communication Technologies, ICECCT 2021

作者： Ahuja, Bharti Doriya, Rajesh National Institute of Technology Raipur Department of IT Raipur India

ISBN: (纸本)9781665414807

the increased demand of multimedia leads to shortage of network bandwidth and memory capacity. As a result, image compression is more significant for decreasing data redundancy, saving storage space and bandwidth. Along with the compression the next major challenge in this field is to safeguard the compressed data further from the spy which are commonly known as hackers. It is evident that the major increments in the fields like communication, wireless sensor network, data science, cloud computing and machine learning not only eases the operations of the related field but also increases the challenges as well. this paper proposes a worthy composition for image compression encryption based on unsupervised learning i.e. k-means clustering for compression with logistic chaotic map for encryption. the main advantage of the above combination is to address the problem of data storage and the security of the visual data as well. the algorithm reduces the size of the input image and also gives the larger key space for encryption. the validity of the algorithm is testified with the PSNR, MSE, SSIM and Correlation coefficient. © 2021 IEEE.

关键词： Cryptography

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Content-adaptive postfiltering for very low bit rate video

Content-adaptive postfiltering for very low bit rate video

引用

7th data compression conference / 4th Annual Industry Workshop on image compression - Applications and Innovation

作者： Jacquin, A Okada, H Crouch, P Bell Lab Murray Hill United States

ISBN: (纸本)0818677619

We propose a postfiltering algorithm which adapts to global image quality as well as (optionally) to semantic image content extracted from the video sequence. this approach is in contrast to traditional postfiltering techniques which attempt to remove coding artifacts based on local signal characteristics only. Our postfilter is ideally suited to bead-and-shoulders video coded at very low bit rates (less than 25.6 kbps), where coding artifacts are fairly strong and difficult to distinguish from fine image detail. Results are shown comparing head-and-shoulder sequences encoded at 16 kbps with an H.263-based codec to images postfiltered using the content-adaptive postfilter proposed here. the postfilter manages to remove most of the mosquito artifacts introduced by the low-bit-rate coder while preserving a good rendition of facial detail.

关键词： image coding

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compression of Medical image using Wavelet based Sparsification and coding 4

Compression of Medical Image using Wavelet based Sparsificat...

引用

4th International conference on Signal Processing and Integrated Networks (SPIN)

作者： Patbhajel, Utpreksh Kumar, Ranjeet Kumar, A. Lee, H. -N. PDPM Indian Inst Informat Technol Design & Mfg Elect & Commun Engn Jabalpur 482005 MP India Gwangju Inst Sci & Technol Sch Elect & Comp Sci Gwangju 500712 South Korea

ISBN: (纸本)9781509027972

In this paper, medical image compression technique is presented based on adaptive Scan Wavelet Difference Reduction (ASWDR). It helps to save the storage space and transmission bandwidth of tele-healthcare system. the presented compression scheme has evaluated for different ultrasound image of different cases. the ASWDR technique is exploited with different wavelet filters and obtained the different efficiency of compression as per distinctive sparse characteristics. However, the performance of presented compression scheme is evaluated with fidelity assessments as well as human vision perception for compression and reconstruction. As seen the results, compression of the image is obtained up to 45:1 with 99% of structural similarity of the original and compressed image.

关键词： image compression WDR Wavelets Big data

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Study of image compression Based on Wavelet Transform

Study of Image Compression Based on Wavelet Transform

引用

4th International conference on Intelligent Systems Design and Engineering Applications (ISDEA)

作者： Wang Yannan Zhang Shudong Liu Hui Capital Normal Univ Coll Informat Engn Beijing 100048 Peoples R China

ISBN: (纸本)9781479927913

the key technology of image compression is that image data is transformed, the transformed data is quantized and the quantized data is entropy coding. Using wavelet image compression is a common method of image compression, and this paper uses wavelet transform, multi-resolution analysis and quantization and coding of different scale wavelet coefficients to achieve image compression. And at the same time, the paper adopts two different methods that the first method is to take the low frequency and abandon high frequency and the second method is the threshold method to achieve image compression. For the threshold method, it also takes different research programs in order to achieve high image compression.

关键词： Wavelet Transform image compression Wavelet Coefficients Quantization coding

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Color image data compression in multimedia

Color image data compression in multimedia

引用

4th International conference on Electrical and Computer Engineering

作者： Koli, Nitin A. Ali, Mir Sadique PRM Inst Technol & Res Dept Comp Sci Badnera India SGB Amarvati Univ Amravati India

ISBN: (纸本)9789843238146

Immense color image data has to handle in multimedia processing, so huge storage space is required. To overcome the problem of color image data storage management, color image data compression is necessary. this paper presents the approach based on Fractal coding which falls in the lossy compression category. Proposed approach firstly, separates the three color planes of RGB color space images and then the grey level Fractal coding algorithm is applied on individual planes independently. Proposed approach is implemented for the numerous indoor and outdoor color images. Implementations are carried out with different size of domain blocks and range blocks. Encoding and decoding time, image compression ratio and peak signal to noise ratio parameters are used for the performance evaluation. Results are compared and represented with the performance graph. Implementation results show that smaller compression ratio with higher reconstruction quality can be achieved with smaller domain blocks and vice versa. the proposed approach can be useful according to the individuals' requirement of compression ratio and image reconstruction quality for the huge color image database in multimedia. the encoding time of proposed approach is more in comparison with the decoding time but more competitive with respect to the compression ratio in comparison with the existing color image compression standards.

关键词： image compression

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Efficient context-based entropy coding for lossy wavelet image compression

Efficient context-based entropy coding for lossy wavelet ima...

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7th data compression conference / 4th Annual Industry Workshop on image compression - Applications and Innovation

作者： Chrysafis, C Ortega, A Univ of Southern California Los Angeles United States

ISBN: (纸本)0818677619

In this paper we present an adaptive image coding algorithm based on novel backward-adaptive quantization/classification techniques. We use a simple uniform scalar quantizer to quantize the image subbands. Our algorithm puts coefficient into one of several classes depending on the values of neighboring previously quantized coefficients. these previously quantized coefficients form contexts which are used to characterize the subband data. To each context type corresponds a different probability model and thus each subband coefficient is compressed with an arithmetic coder having the appropriate model depending on that coefficient's neighborhood. We show how the context selection can be driven by rate-distortion criteria, by choosing the contexts in a way that the total distortion for a given bit rate is minimized. Moreover the probability models for each context are initialized/updated in a very efficient way so that practically no overhead information has to be sent to the decoder. Our results are comparable or in some cases better than the recent state of the art, with our algorithm being simpler than most of the published algorithms of comparable performance.

关键词： image coding

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Aligning images with CAD Models via Quaternion Optimization

Aligning Images with CAD Models via Quaternion Optimization

引用

conference on mathematics of data/image Pattern coding, compression, and encryption with Applications XIII

作者： Stiller, Peter F. Texas A&M Univ Dept Math College Stn TX 77843 USA

ISBN: (纸本)9780819487469

this paper introduces an algorithm for "mapping" locations in a 2D image of an object onto a 3D CAD model of that object. the goal is to align the image with the CAD model so that the location of various points in the image can be found on the object. We will actually present two methods for achieving this goal. One relies on projective invariants and requires no information about the camera parameters. Unfortunately, its performance is sometimes erratic in the face of particular types of errors. the other method assumes that the user is able to identify a minimum of 4 feature points in the image and the corresponding points on the CAD model. Beyond that, no information is assumed except for knowledge of the size of the camera's CCD and the location of the center of projection in the image. this second algorithm is highly accurate and robust in the face of real-world errors. We call this second algorithm the quaternion optimization algorithm. It positions the camera in CAD space so as to optimally align the matched features. this in turn permits the mapping of other image pixels to the CAD model.

关键词： Computer aided design Solid modeling Cameras 3D modeling CCD cameras Optimization (mathematics) Motion models 3D image processing Mathematical modeling Coded apertures

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Convex Optimization based Sparse Dictionary Learning for image compression 4

Convex Optimization based Sparse Dictionary Learning for Ima...

引用

4th International conference on Signal Processing and Integrated Networks (SPIN)

作者： Keni, Nishant Deepak Ansari, Rizwan Ahmed Veermata Jijabai Technol Inst Dept Elect Engn Bombay Maharashtra India Indian Inst Technol Ctr Studies Resources Engn Bombay Maharashtra India

ISBN: (纸本)9781509027972

Sparse representation using over-complete dictionaries have shown to produce good quality results in various image processing tasks. Dictionary learning algorithms have made it possible to engineer data adaptive dictionaries which have promising applications in image compression and image enhancement. the most common sparse dictionary learning algorithms use the techniques of matching pursuit and K-SVD iteratively for sparse coding and dictionary learning respectively. While this technique produces good results, it requires a large number of iterations to converge to an optimal solution. In this article, we propose a closed form convex optimization technique for both sparse coding and dictionary learning. the approach results in providing the best possible dictionary and the sparsest representation resulting in minimum reconstruction error which in turn results in compression. It is clearly seen from the results that the proposed algorithm provides much better reconstruction results than conventional sparse dictionary techniques for a fixed number of iterations. Depending upon the amount of details present in the image, the proposed algorithm is seen to reach the optimal solution with significantly lower number of iterations. Consequently low mean squared error is obtained using the proposed algorithm. We demonstrate the results with standard image.

关键词： sparse coding dictionary learning normal equation convex optimization image compression

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