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Hybrid fractal-Wavelet Method for Multi-Channel EEG Signal Compression

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2014年第8期33卷 2583-2604页

作者： Saeedi, Jamal Faez, Karim Moradi, Mohammad Hassan Amirkabir Univ Technol Dept Elect Engn Tehran Polytech Tehran Iran Amirkabir Univ Technol Dept Biomed Engn Tehran Polytech Tehran Iran

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.

关键词： Electroencephalograms Compression fractal coding Wavelet-based coding Multi-objective genetic optimization

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A multiresolution distance measure for images

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IEEE SIGNAL PROCESSING LETTERS 1998年第6期5卷 138-140页

作者： Juffs, P Beggs, E Deravi, F Univ Wales Dept Elect & Elect Engn Swansea SA2 8PP W Glam Wales Univ Wales Dept Math Swansea SA2 8PP W Glam Wales

We present a new distance measure that can be used for comparing digital images. The proposed grey block distance (GBD) is compared with the Hutchinson metric to show its usefulness as a measure of the visual similari... 详细信息

关键词： distance measures fractal coding Haar decomposition Hausdorff distance Hutchinson metric

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A fractal-based clustering approach in large visual database systems

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MULTIMEDIA TOOLS AND APPLICATIONS 1996年第3期3卷 225-244页

作者： Zhang, AD Cheng, BA Acharya, R SUNY BUFFALO DEPT ELECT & COMP ENGN BUFFALO NY 14260 USA

Large visual database systems require effective and efficient ways of indexing and accessing visual data on the basis of content. In this process, significant features must first be extracted from image data in their pixel format. These features must then be classified and indexed to assist efficient access to image content. With the large volume of visual data stored in a visual database, image classification is a critical step to achieve efficient indexing and retrieval. In this paper, we investigate an effective approach to the clustering of image data based on the technique of fractal image coding, a method first introduced in conjunction with fractal image compression technique. A joint fractal coding technique, applicable to pairs of images, is used to determine the degree of their similarity. Images in a visual database can be categorized in clusters on the basis of their similarity to a set of iconic images. Classification metrics are proposed for the measurement of the extent of similarity among images. By experimenting on a large set of texture and natural images, we demonstrate the applicability of these metrics and the proposed clustering technique to various visual database applications.

关键词： content-based image retrieval fractal coding image clustering texture and image database systems

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A fractals-inspired approach to binary image database indexing and retrieval

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ANNALS OF TELECOMMUNICATIONS-ANNALES DES TELECOMMUNICATIONS 2000年第3-4期55卷 194-200页

作者： Vissac, M Dugelay, JL Rose, K Inst Eurecom Dept Multimedia Commun F-06904 Sophia Antipolis France Univ Calif Santa Barbara SCL Dept Elect & Comp Engn Santa Barbara CA USA

This paper applies ideas from fractal compression and optimization theory to attack the problem of efficient content-based image indexing and retrieval. Similarity of images is measured by block matching after optimal (geometric, photometric, etc.) transformation. Such block matching which, by definition, consists of localized optimization, is further governed by a global dynamic programming technique. (Viterbi algorithm) that ensures continuity and coherence of the localized block matching results. Thus, the overall optimal transformation relating two images is determined by a combination of local block-transformation operations subject to a regularization constraint. Experimental results on some limited subsets of still binary images from the MPEG-7 database demonstrate the power and potential of the proposed approach.

关键词： image database image analysis image recognition indexing information retrieval similarity fractal coding still image binary image

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Combining fractal image compression and vector quantization

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2000年第2期9卷 197-208页

作者： Hamzaoui, R Saupe, D Univ Leipzig Inst Informat D-04109 Leipzig Germany

In fractal image compression, the code is an efficient binary representation of a contractive mapping whose unique fixed point approximates the original image. The mapping is typically composed of affine transformations, each approximating a block of the image by another block (called domain block) selected from the same image. The search for a suitable domain block is time-consuming. Moreover, the rate-distortion performance of most fractal image coders is not satisfactory. We show how a few fixed vectors designed from a set of training images by a clustering algorithm accelerate the search for the domain blocks and improve both the rate-distortion performance and the decoding speed of a pure fractal coder, when they are used as a supplementary vector quantization codebook. We implemented two quadtree-based schemes: a fast top-dawn heuristic technique and one optimized with a Lagrange multiplier method. For the 8 bits per pixel (bpp) luminance part of the 512 x 512 Lenna image, our best scheme achieved a peak-signal-to-noise ratio of 32.50 dB at 0.25 bpp.

关键词： clustering fractal coding Lagrange multipliers mean shape-gain vector quantization quadtrees

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Low-complexity fractal-based image compression using two-stage search strategy

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OPTICAL ENGINEERING 1999年第6期38卷 1006-1013页

作者： Wang, CC Chen, CH Natl Cheng Kung Univ Dept Elect Engn Tainan 70101 Taiwan

A fractal image compression scheme is presented which incorporates the vector quantizer (VQ) to reduce the computational complexity in the encoding phase. The high-detail blocks of an input image are approximated by a fast fractal coding, and the low-detail blocks are encoded by the VQ technique. In fractal image coding, most of the time is spent on finding a close match between a range block and a large pool of domain blocks. We propose a two-stage search algorithm to reduce the search space of the domain pool. First, a fast and simple binary pattern matching algorithm is proposed to extract a small pool of candidate domains, and then the gray-level-matching algorithm is used to find the best match from the candidates. In addition, a variable block-size segmentation method is used in our coding system to further improve the image quality. It is shown that the average encoding time is short, and the average speedup factor of 45 is achieved, as compared to the full search fractal coding. Simulation results also show that the proposed scheme can achieve better image quality and higher compression ratio than other fast fractal-based coding schemes. (C) 1999 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(99)00606-6].

关键词： image compression fractal coding vector quantization image processing

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Block loss recovery using fractal extrapolation for fractal-coded images

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2002年第6期E85D卷 1052-1053页

作者： Kim, SH Noh, YN Jang, IH Kim, NC Youngsan Univ Dept Multimedia Engn Yangsan 626847 South Korea LG Elect Digital Network Display Res Lab Kumi 730727 South Korea Kyungwoon Univ Dept Elect Engn Kumi 730850 South Korea Kyungpook Natl Univ Dept Elect Engn Taegu 702701 South Korea

A new algorithm is presented for recovering the blocks lost with the cell loss in the ATM transmission of the images coded by Jacquin's fractal coding. The key technique of the proposed BLRA (block loss recovery algorithm) is a fractal extrapolation that estimates the pixels in a lost block by rising the contractive mapping parameters of a range block homogenous to the lost block. The proposed BLRA is applied to the lost blocks in the iteration of decoding.

关键词： image coding fractal coding block loss recovery fractal extrapolation

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fractal Image Compression Based on Numbers of Hopping and Variance of Continuing Positive and Negative Pixels

Fractal Image Compression Based on Numbers of Hopping and Va...

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9th International Conference for Young Computer Scientists

作者： Qin, Zhen Yu, Hai Ju, Jinling Liaoning Shihua Univ Sch Comp & Commun Engn Liaoning Peoples R China Northeastern Univ Software Coll Shenyang Peoples R China Northeastern Univ Coll Sci & Informat Engn Shenyang Peoples R China

ISBN: (纸本)9781424441983

In the present paper a fast and efficient fractal image encoding method based on sorting the contracted domain pool is presented. Two parameters are used to sort domain pool: the number of hopping and the variance of continuing positive and negative pixels in the given block. With the help of the parameters, the number of domain blocks examined by a range block is reduced dramatically, and thus, the sort of domain blocks results in a considerable acceleration of the encoding process. To compare with the method done by *** that sorts the contracted domain pool in terms of their local variances, the proposed method is proved to be a better way to improve the quality of pictures with a little more time in encoding.

关键词： fractal coding image coding matching method

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Wavelet Based Fast fractal Image Compression

Wavelet Based Fast Fractal Image Compression

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International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)

作者： Borkar, Ekta Gokhale, A. V. Yeshwantrao Chavan Coll Engn Dept Elect Engn Nagpur Maharashtra India

ISBN: (纸本)9781509032945

Image compression is a significant technology in the transmission and storage of digital images. The importance of image compression is that to preserve the visual feature of the image. One of the finest image compression techniques is using wavelet transform which have comparatively had several benefits over other. Basically wavelets are confined in both time and frequency. Wavelet transformations perform multilevel decomposition of image that is diving image into sub parts of image at different measures. Discrete wavelet transform examined the signal at a different frequency bandwidth that is approximate band and detail band. Using wavelet with balance resolution at any time and frequency gives a better signal illustration using multilevel analysis. Therefore, at very low bit rate the suggested method improves the visual feature of decoded image.

关键词： Image compression fractal coding wavelet transform

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Improving quality of fractal compressed images

Improving quality of Fractal compressed images

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International Conference on Machine Vision

作者： Nademejad, E. hassanpour, H. Salarian, M. Univ Mazandaran Noushirvani Inst Technol Dept Comp & Elect Engn Babol Sar Iran

ISBN: (纸本)9781424416240

This paper proposes a new quality improvement technique for fractal-based image compression techniques using diffusion equations. fractal coding uses a contractive mapping scheme to represent an image. This process of contractive mapping causes artifacts and blocking effects in encoded images. This problem is severed when compression ratio is increased or there are high frequency regions in the image. Hence, to amulet the deficiency of fractal coding approaches in image compression, we propose using diffusion equations as a post processor. Diffusion equations are powerful tools for image enhancement. This technique has been examined on a variety of standard images. The obtained results indicate that the proposed method improves performance of fractal-based image compression techniques.

关键词： fractal coding quality image diffusion equations

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