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Fast Fractal Image Coding Based on Fractional Box-counting Dimension
基于分数盒维数的快速分形图像编码

HE Chuan-jiang,HUANG Juan-juan,LI Gao-ping,
何传江
,黄娟娟,李高平

中国图象图形学报 , 2007,
Abstract: Fractal image coding is a very promising compression technique,but it suffers from long encoding time.The time to encode fractally an image is mostly spent on searching for the best-matched block for each of range blocks in a usually-large domain pool.This paper thus proposed a fast fractal encoding algorithm based on fractional box-counting dimension of an image block,which can find out the best-matched block for an input range block with a reduced search.Experimental results show that the proposed algorithm can significantly shorten the encoding time,while achieving the same or better decoded image quality as baseline fractal algorithm with full search.
Secure Fractal Image Coding  [PDF]
Shiguo Lian
Computer Science , 2007,
Abstract: In recent work, various fractal image coding methods are reported, which adopt the self-similarity of images to compress the size of images. However, till now, no solutions for the security of fractal encoded images have been provided. In this paper, a secure fractal image coding scheme is proposed and evaluated, which encrypts some of the fractal parameters during fractal encoding, and thus, produces the encrypted and encoded image. The encrypted image can only be recovered by the correct key. To keep secure and efficient, only the suitable parameters are selected and encrypted through in-vestigating the properties of various fractal parameters, including parameter space, parameter distribu-tion and parameter sensitivity. The encryption process does not change the file format, keeps secure in perception, and costs little time or computational resources. These properties make it suitable for secure image encoding or transmission.
AN IMPROVED DOMAIN CLASSIFICATION SCHEME BASED ON LOCAL FRACTAL DIMENSION
JAYAMOHAN M.,K. REVATHY
Indian Journal of Computer Science and Engineering , 2012,
Abstract: In fractal image compression, most of the time during encoding is spent for finding the best matching pair of range-domain blocks. Different techniques have been analyzed for decreasing the number of operations required for this range-domain matching. Encoding time can be saved by reducing the domain search pool for each range block. Domain blocks can be classified based on local fractal dimension. Fractal dimension is being studied as a measure to analyze the complexity of image portions. This paper proposes application of height balanced binary search trees for storing domain information ordered in terms of the local fractal dimension. The approach is toprepare the domain pool dynamically, by comparing the fractal dimension of range block with that of the domains. Domains with fractal dimension in an interval, evenly covering the fractal dimension of range block alone are given for comparison. We use AVL trees to enlist the domains based on their fractal dimension. Thedomain pool is prepared at runtime. Since the tree organization is used in the preprocessing phase, the proposed method can be used with any algorithm for fractal compression.
Fractal Image Coding with Digital Watermarks
M. Candik,D. Levicky,Z. Klenovicova
Radioengineering , 2000,
Abstract: In this paper are presented some results of implementation of digitalwatermarking methods into image coding based on fractal principles. Thepaper focuses on two possible approaches of embedding digitalwatermarks into fractal code of images - embedding digital watermarksinto parameters for position of similar blocks and coefficients ofblock similarity. Both algorithms were analyzed and verified on grayscale static images.
Color Image Compression with Modified Fractal Coding on Spiral Architecture  [cached]
Nileshsingh V. Thakur,O. G. Kakde
Journal of Multimedia , 2007, DOI: 10.4304/jmm.2.4.55-66
Abstract: The proposed approach (CICMFCSA), firstly, compose the one-plane image using the pixel’s trichromatic coefficients. One-plane image in traditional square structure is represented in Spiral Architecture for compression. On this Spiral Architecture image, proposed modified Fractal grey level image coding algorithm (MFCSA) is applied to get encoded image. In this modified Fractal coding, the numbers of domain blocks are optimized from 343 to 10 using local search. Extensive experiments are carried out on UCID - An Uncompressed Color Image Database. The proposed approach minimizes the encoding process time because of optimized domain blocks and one dimensional structure of Spiral Architecture and falls in the lossy compression category. The results of SFC and our approach are compared with respect to the time.
Trigonometric Approximation in Fractal Image Coding
M. Candik
Radioengineering , 2001,
Abstract: In this paper is presented a new approach in fractal image codingbased on trigonometric approximation. The least square approximationmethod is used for approximation of blocks in standard fractal imagecompression algorithm. In the paper is shown that it is possible to usealso trigonometric approximation for describing of blocks in fractalimage coding. This approximation was implemented and analyzed frompoint of view of quality of reconstructed images. The experimentalresults of this method were tested on static grayscale images.
Some Modifications of Fractal Image Coding
D. Levicky,M. Candik,R. Pundzak
Radioengineering , 1999,
Abstract: In this paper some modifications of fractal image coding are presented. Proposed methods are based on correlation coefficients computing as an alternative approach to searching of similarity between blocks. The convergence speed of decoding process is faster then convergence speed of standard method. The convergence process with modified start conditions of decoding process are analysed and verified on gray scale static images too.
Fractal Image Coding
分形图象编码

He Aijun,Ma Zhengming,
何爱军
,马争鸣

中国图象图形学报 , 1999,
Abstract: This is an overview on fractal image coding. On the base of collecting and reading related documents, we describe the current research status of fractal image coding and make a remark on its prospect.
A Proposed method for EDGE Detection of and Image Based on Self-Similarity Parameterisation by Fractal Coding  [PDF]
Sri Shimal Das,Dr. Dibyendu Ghoshal
International Journal of Computer Technology and Applications , 2011,
Abstract: Detecting edges is a basic operation in image processing. The edges of items in an image hold much of the information in the image. Fractal based image coding gives some desirable properties like resolution independence, fast decoding, and very competitive rate-distortion curves. For any image edges are the foundation of image texture and shape figure extraction. In this paper we propose a method for edge detection of an image based on self-similarity of fractal coding parameterisation. From the experimental result we discovered that mean-square-error distance (MSE) can be used to extract edge of fractal image very effectively. The self-similarity coefficient between the local range block and the searching domain block is centered at the current pixel being processed and nearcenter self-affine transform is applied in local searching process, finally a binary operator is used to threshold its magnitude and produce the edge map of the image. The results of experiments show that the proposed method for edge detection is valid and effective.
Several Remarks on Fractal Image Block Coding
L. Dedera,J. Chmurny
Radioengineering , 1997,
Abstract: In this paper the dependence of PSNR on the size of both a codebook pool and range blocks is compared. The statistical properties of the values of transformation coefficients and distances between coded range blocks and optimal domain blocks in the fractal image block coding scheme are discussed.
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