• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.505-510
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• 2018

In this study, we allocate bits by quantizing these fractal coefficients through a quantizer which can extract the probability distribution. In the coding process of IFS, a variable size block method is used to shorten the coding time and improve the compression ratio. In the future, it will be necessary to further improve the coding time and the compression rate while maintaining the best image quality in the fractal coding process.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.179-187
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• 2000

Fractal theory has strengths such as high compression rate and fast decoding time in application to image compression, but it suffers from long comparison time necessary for finding an optimally similar domain block in the encoding stage. This paper proposes a neural network based block classifier which enhances the encoding time significantly by classifying domain blocks into 4 patterns and searching only those blocks having the same pattern with the range block to be encoded. Size of a block is differently determined depending on the image complexity of the block. The proposed algorithm has been tested with three different images having various featrues. The experimental results have shown that the proposed algorithm enhances the compression time by 40% on average compared to the conventional fractal encoding algorithms, while maintaining allowable image qualify of PSNR 30 dB.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.38-46
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• 1999

In this paper, the fractal image compression using the minimizing method of domain region is proposed. It is minimize to domain regions in the process of decoding. Since the conventional fractal decoding applies to IFS(iterative function system) for the total range blocks of the decoded image, its computational complexity is a vast amount. In order to improve this using the number of the referenced times to the domain blocks for the each range blocks, a classification method which divides necessary and unnecessary regions for IFS is suggested. If necessary regions for IFS are reduced, the computational complexity is reduced. The proposed method is to define the minimum domain region that a necessary region for IFS is minimized in the encoding algorithms. That is, a searched region of the domain is limited to the range regions that is similar with the domain regions. So, the domain region is more overlapped. Therefore, there is not influence on image quality or PSNR(peak signal-to-noise ratio). And it can be a fast decoding by reduce the computational complexity for IFS in fractal image decoding.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1317-1328
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• 1996

In this paper, we propose a fast image coding algorithm to shorten long time to take on fractal image encoding. For its Performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make the corresponding image to be compared with. Them, the whole area of the contracted image is searched in order to find the fixed point of contractive transformation of the orignal image corresponding to the contracted image. It needs a lot of searching time on encoding However, the proposed algorithm considerable reduces encoding time by using scaling method and limited search area method. On comparison of the proposed algorithm with Joaquin's method, the proposed algorithm is at least 180 times as fast as that of Jacquin's method on encoding time with a little degradation of the decoded image quality and a little increase of the compression rate. There-for, it is found that the proposed algorithm largely improves the performance in the aspect of encoding time when compared with other fractal image coding methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.110-116
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• 2008

This paper presents a new postprocessing method to eliminate the false minutiae, that caused by the skelectonization of fingerprint image, and an image compression method using Isometric Self Organizing Map(ISOSOM). Since the SOM has simple structure, fast encoding time, and relatively good classification characteristics, many image processing areas adopt this such as image compression and pattern classification, etc. But, the SOM shows limited performances in pattern classification because of it's single layer structure. To maximize the performance of the pattern classification with small code book, we a lied the Isometric SOM with the isometry of the fractal theory. The proposed Isometric SOM postprocessing and compression algorithm of fingerprint image showed good performances in the elimination of false minutiae and the image compression simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.708-714
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• 2000

In this paper, an one-dimensional VLSI array for high speed processing of fractal image compression algorithm based the quad-tree partitioning method is proposed. First of all, the single assignment code algorithm is derived from the sequential Fisher's algorithm, and then the data dependence graph(DG) is obtained. The two-dimension array is designed by projecting this DG along the optimal direction and the one-dimensional VLSI array is designed by transforming the obtained two-dimensional array. The number of Input/Output pins in the designed one-dimensional array can be reduced and the architecture of process elements(PEs) can he simplified by sharing the input pins of range and domain blocks and internal arithmetic units of PEs. Also, the utilization of PEs can be increased by reusing PEs for operations to the each block-size. For fractal image compression of 512X512gray-scale image, the proposed array can be processed fastly about 67 times more than sequential algorithm. The operations of the proposed one-dimensional VLSI array are verified by the computer simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.45-55
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• 1994

In this paper, a block based image approximation technique using the Self Affine System(SAS) from the fractal theory is suggested. Each block of an image is divided into 4 tiles and 4 affine mapping coefficients are found for each tile. To find the affine mapping cefficients that minimize the error between the affine transformed image block and the reconstructed image block, the matrix euation is solved by setting each partial differential coefficients to aero. And to ensure the convergence of coding block. 4 uniformly partitioned affine transformation is applied. Variable block size technique is employed in order to applynatural image reconstruction property of fractal image coding. Large blocks are used for encoding smooth backgrounds to yield high compression efficiency and texture and edge blocks are divided into smaller blocks to preserve the block detail. Affine mapping coefficinets are found for each block having 16$\times$16, 8$\times$8 or 4$\times$4 size. Each block is classified as shade, texture or edge. Average gray level is transmitted for shade bolcks, and coefficients are found for texture and edge blocks. Coefficients are quantized and only 16 bytes per block are transmitted. Using the proposed algorithm, the computational load increases linearly in proportion to image size. PSNR of 31.58dB is obtained as the result using 512$\times$512, 8 bits per pixel Lena image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2789-2800
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• 1996

Real time fractal coding for successive QCIF 144*176 luminance images has been implemented on a 50MHz IBM 486 personal computer. To satisfy the frame encoding speed and data compression ratio, following algorithms are adopted. In order to minimize encoding time, extension SAS being not searching of domain blocks is used. for reducing the bits per pixel, conventioal 4*4 range block is extended to 8*8 range block. and range block extension decrease quality of decoded image. For improvement quality of decoded image, the paper apply quad-tree partition mothod. In order to divide **8 range block, self-simiarity is compared 8*8 range block with spatial contractive transformed 8*8 domain block. According to self-simiarity, the block is partitioned and owing to block partition, increased encoding time is minimized. According to self-simiarity of 8*8 range block and spatial contractive transformed 8*8 domain block, number of fractal factor is varied. Simultaneously with minimizing the decrement of decoded image's quality, transmittion rate and encoding time is shorted. The results enable us to process the real-time fractal coding. For the claire test image, the average PSNR was 32.4dB, 0.12 bit rates and 33ms coding time per frame.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.117-122
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• 2000

The fractal image compression is based on the self-similarity that some area in an image is very similar to others. This compression method offers high compression ratio and fast decompression, but it has very long encoding time. To cut-off the encoding time, most researches give a restriction on domain blocks to be compared with a range block or make an effective search sequence of the domain blocks for a range block. However, most of them take much encoding time yet. In this research, we propose an algorithm that greatly reduces the encoding time by considering the coherence between range blocks. This algorithm first classifies all range blocks into some groups using the coherence between range blocks, and then searches corresponding domain blocks only for the key block of each group. If this scheme is joined in a prior work of the other fractal compression algorithm, it will give a great effectiveness to encoding time.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.1057-1065
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• 1998

This paper describes a new fractal image coding algorithm to shorten time to take on fractal image encoding by using limited search area method and scaling method. First, the original image is contracted respectively by half and by quarter with the scaling method. And then, the corresponding domain block of the quarter-sized image which is most similar with one range block of the half-sized image is searched within the limited area in order to reduce the encoding time extremely. This searched block is used in encoding. Also, we propose an algorithm provided much shorter encoding time and better compression ratio with a little degradation of the decoded image quality than Jacquin's method.