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color image compression based on block truncation coding using pattern fitting principle

PATTERN RECOGNITION 2007年第9期40卷 2408-2417页

作者： Dhara, Bibhas Chandra Chanda, Bhabatosh Jadavpur Univ Dept Informat Technol Kolkata 700098 W Bengal India Indian Stat Inst Elect & Commun Sci Unit Kolkata 700108 W Bengal India

This paper describes a color image compression technique based on block truncation coding using pattern fitting (BTC-PF). High degree of correlation between the RGB planes of a color image is reduced by transforming them to O1O2O3 planes. Each O-i plane (1 <= i <= 3) is then encoded using BTC-PF method. Size of the pattern book and the block size are selected based on the information content of the corresponding plane. The result of the proposed method is compared with that of several BTC based methods and the former is found superior. Though this method is a spatial domain technique, it is also compared with JPEG compression method, which is one of most popular frequency domain techniques. It is found that the performance of the proposed method is a little inferior to that of the JPEG in terms of quality of the reconstructed image. Decoding time is another important criterion where the compressed image is decoded frequently for various purposes. As the proposed method requires negligible decoding time compared to JPEG, the former is preferred over the latter in those cases. (c) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： block truncation coding color image compression image fidelity index pattern fitting reversible color transformation

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color image compression using PCA and backpropagation learning

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PATTERN RECOGNITION 2000年第9期33卷 1555-1560页

作者： Clausen, C Wechsler, H George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

The RGB components of a color image contain redundant information that can be reduced using a new hybrid neural-network model based upon Sanger's algorithm for representing an image in terms of principal components and a backpropagation algorithm for restoring the original representation. The PCA method produces a black and white image with the same number of pixels as the original color image, but with each pixel represented by a scalar value instead of a three-dimensional vector of RGB components. Experimental results show that as our hybrid learning method adapts to local (spatial) image characteristics it outperforms the YIQ and YUV standard compression methods. Our experiments also show that it is feasible to apply training results from one image to previously unseen images. (C) 2000 Published by Elsevier Science Ltd.

关键词： principal component analysis (PCA) color image compression backpropagation (BP) learning

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color image compression algorithm based on the DCT transform combined to an adaptive block scanning

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2011年第1期65卷 16-26页

作者： Douak, Fouzi Benzid, Redha Benoudjit, Nabil Univ Batna Fac Engn Dept Elect Batna 05000 Algeria

This paper considers the design of a lossy image compression algorithm dedicated to color still images After a preprocessing step (mean removing and RGB to YCbCr transformation) the DCT transform is applied and followed by an iterative phase (using the bisection method) including the thresholding the quantization dequantization the inverse DCT YCbCr to RGB transform and the mean recovering This is done in order to guarantee that a desired quality (fixed in advance using the well known PSNR metric) is checked For the aim to obtain the best possible compression ratio CR the next step is the application of a proposed adaptive scanning providing for each (n n) DCT block a corresponding (n x n) vector containing the maximum possible run of zeros at its end The last step is the application of a modified systematic lossless encoder The efficiency of the proposed scheme is demonstrated by results especially when faced to the method presented in the recently published paper based on the block truncation coding using pattern fitting principle (C) 2010 Elsevier GmbH All rights reserved

关键词： color image compression YCbCr transform Block based DCT Adaptive scanning Quality controllability

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color image compression using quantization, thresholding, and edge detection techniques all based on the moment-preserving principle

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PATTERN RECOGNITION LETTERS 1998年第2期19卷 205-216页

作者： Yang, CK Tsai, WH Natl Chiao Tung Univ Dept Comp & Informat Sci Hsinchu 300 Taiwan Ming Chuan Univ Dept Informat Management Taipei 111 Taiwan

A new approach to color image compression with high compression ratios and good quality of reconstructed images using quantization, thresholding, and edge detection all based on the moment-preserving principle is proposed, An input image with 24 bits per pixel is quantized into 8 bits per pixel using a new color quantization method based on the moment-preserving principle. The quantized image is then divided into n x n non-overlapping square blocks. Two representative colors for each block are computed by moment-preserving thresholding. A bit-map is then generated, consisting of 0s and 1s indicating whether the block pixels are assigned to the first color or the second according to the Euclidean distance measure. A moment-based edge detector is performed further on the bitmap of each non-uniform block. The two parameters iota and theta of a line edge with the equation of x cos theta + gamma sin theta = iota are obtained. The image is finally coded with a codebook of a 256-color palette;a 1-bit indicator for each block which specifies whether the block is uniform or not;an 8-bit color index for a uniform block, or two 8-bit color indices, a 3-bit index for theta, and a 2-bit or 3-bit index for iota for a non-uniform block. An average compression ratio of 22.49 or 33.32 can be obtained for 4 x 4 or 5 x 5 image blocks, respectively. Experimental results show the feasibility and efficiency of the proposed approach for color image compression. (C) 1998 Elsevier Science B.V, All rights reserved.

关键词： color image compression color quantization bit-map moment-preserving principle

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color image compression by moment-preserving and block truncation coding techniques

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IEEE TRANSACTIONS ON COMMUNICATIONS 1997年第12期45卷 1513-1516页

作者： Yang, CK Lin, JC Tsai, WH NATL TSING HUA UNIV DEPT COMP & INFORMAT SCIHSINCHU 300TAIWAN

A new color image compression technique based on moment-preserving and block truncation coding is proposed, An input image is divided into nonoverlapping blocks and each block pixel is assigned one of two representative colors, which are computed with analytic formulas derived from preserving certain moments in the block. A bit map is then generated for each block to represent the pixels' colors, Different uniformity conditions in the representative colors are also identified and utilized to save code bits, Good average compression ratios up to about 13 can be achieved, as shown by experimental results.

关键词： bit map block truncation coding color image compression moment-preserving uniform color plane

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color image compression Using JPEG2000 With Adaptive color Space Transform

Color Image Compression Using JPEG2000 With Adaptive Color S...

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International Conference on Electronics and Communication Systems (ICECS)

作者： Sebastian, Stephy Manimekalai, M. A. P. Karunya Univ Dept ECE Coimbatore Tamil Nadu India

ISBN: (纸本)9781479966387

This paper presents a study of color image compression based JPEG 2000 with color space transform and comparison with JPEG compression. The basis for the JPEG algorithm is the Discrete Cosine Transform (DCT) which extracts spatial frequency information from the spatial amplitude samples. These frequency components are then quantized to eliminate the visual data from the image that is least perceptually apparent, thereby reducing the amount of information that must be stored. Finally, the redundant properties of the quantized frequency samples are exploited through Huffman coding to produce the compressed representation. The JPEG-2000 which is based on the wavelet transform is a promising image compression technique expected to replace the current discrete cosine transform based compression known as JPEG. The approach based on JPEG 2000 has better compression performance. It has better compression ratio, good PSNR and low mean square error compared to JPEG compression.

关键词： color image compression DCT DWT Modified JPEG 2000 PSNR compression Ratio Mean Square Error

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color image compression Based on Wavelet Transform and Support Vector Regression WSVR for color image compression 1

Color Image Compression Based on Wavelet Transform and Suppo...

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Conference on First International image Processing, Applications and Systems

作者： Zikiou, Nadia Lahdir, Mourad Ameur, Soltane Univ Mouloud Mammeri UMMTO Dept Elect LAMPA Tizi Ouzou Algeria

ISBN: (纸本)9781479970698

Recent years have seen tremendous increase in the production, transportation and storage of color images. A new method for loss less image compression of color images is presented in this paper. This method is based on wavelet transform and support vector machines (SVM). The wavelet transform is applied to the luminance (Y) and chrominance (Cb, Cr) components of the original color image. Then SVM regression dependence could learn from training data and compression achieved using less training point (support vector) to represent the original data and eliminate redundancy. In addition, an effective entropy coder based on run-length and arithmetic encoders is used to encode vector and weight support. Our compression algorithm is applied to a test set of images of size 1024 * 1024 encoded on 24 bits. To evaluate our results, we calculated the peak signal noise ratio (PSNR) and their ratios datasets compression (CR). Experimental results show that the performance of the compression algorithm to achieve much improvement.

关键词： color image compression Wavelet Transform Support Vector Regression (SVR) Run-length Arithmetic coding PSNR

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color image compression Based on Feature Extraction 8th

Color Image Compression Based on Feature Extraction

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8th International Conference on Soft Computing and Pattern Recognition (SoCPaR) / 8th International Conference on Computational Aspects of Social Networks (CASoN)

作者： Pabi, D. J. Ashpin Aruna, P. Puviarasan, N. Annamalai Univ Dept Comp Sci & Engn Chidambaram Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

This paper proposes an efficient compression scheme for compressing RGB color images based on feature extraction with the combination of DCT transform and the Peano-Hilbert Scan. The RGB color image is converted into YCbCr in order to extract the color and the texture features. The DCT transform is applied to the extracted luma and the chroma component to reduce the redundancy. Peano-Hilbert scanning is performed over the DCT matrix which increases the PSNR of the reconstructed image. The proposed bi-mode quantization is applied to preserve the image quality. The quantized coefficients are encoded using the lossless Huffman encoding. The efficiency of the proposed compression scheme has been implemented and compared with other existing compression techniques. The proposed compression method can achieve a higher fidelity and faster decompression time compared to other lossy compression methods. Thus, compression based on feature extraction contributes to better performance.

关键词： color image compression YCbCr transform color and texture feature extraction DCT transform Quantization Zig-Zag scan Peano-Hilbert scan

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color image compression using a Learned Dictionary of Pairs of Orthonormal Bases

Color Image Compression using a Learned Dictionary of Pairs ...

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Data compression Conference (DCC)

作者： Hou, Xin Gurumoorthy, Karthik S. Rajwade, Ajit Univ Florida Dept ECE Gainesville FL 32611 USA

ISBN: (纸本)9780769543529

We present efficient machine learning methods for color image compression which simultaneously learn bases for compact image representation as well as the color space. We show the benefits of representing color image patches as 2D matrices of size n x 3 n rather than as 3D patches of size n x n x 3. We also present a method to leverage greater representational power from a learned dictionary without increasing its size.

关键词： color image compression color space machine learning orthonormal bases color spaces image compression Data compression Orthogonal color image Artificial Intelligence Machine Learning Dictionaries as Topic Alkali Base materials image representation Bases

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color image compression: Multiwavelets vs. scalar wavelets

Color image compression: Multiwavelets vs. scalar wavelets

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Rout, S Bell, AE Virginia Tech Dept Elect & Comp Engn Blacksburg VA 24061 USA

ISBN: (纸本)0780374029

Recently developed balanced multiwavelets have proven effective for image compression;however, their performance falls slightly short of the scalar wavelets. A previous comparison of some scalar wavelet and multiwavelet, properties illustrated their importance for grayscale image compression. In this paper we present another property: the perfect reconstruction (PR) property;it too appears to explain the performance differences. This paper compares the compression performance of 3 scalar wavelets and 5 balanced multiwavelets on 7 color images. We observe that SA(4) depicts the best performance amongst the multiwavelets in terms of both subjective quality and PSNR;this matches our expectation based on our results that indicate that it is the only BMW which satisfies the PR conditions. Although SA(4) rivals the biorthogonal scalar wavelets in terms of many desirable properties, it suffers from a lower balancing/vanishing order. This difference explains the 0.01-0.47 dB performance gap between the best scalar wavelet and the best balanced multiwavelet.

关键词： image colour analysis image reconstruction wavelet transforms transform coding image coding data compression color image compression balanced multiwavelets scalar wavelets grayscale image compression perfect reconstruction property compression performance subjective quality PSNR biorthogonal scalar wavelets balancing/vanishing order

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