• The Journal of Natural Sciences
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• v.4
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• pp.191-220
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• 1991

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.64-69
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• 2000

This paper proposes a novel fractal coding method for fast encoding and high compression to shorten time to take on fractal encoding by using limited search area. First. the original image is contracted respectively by half and by quarter with the scaling method and bit-plane 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. As the result of the evaluation, the proposed algorithm provided much shorter encoding time and better compression ratio with a little degradation of the decoded image qualify than Jacquin's method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.434-440
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.185-193
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• 1998

Fractal-based monochrome image coding method can be easily applied for color image compression by splitting the color image into different primary spectral channels such as RGB, YIQ or $YC_bC_r$, and encoding each channel independently According to this method, it needs to repeat the fractal coding for each channel, so it have the problem of encoding time. In this paper, a fractal-based coder for color still image is proposed which features the enhancement of compression rate and the reduction of coding time. As the result of the experiment where the proposed algorithm is applied far color images, the compression rate is enhanced by 28 : 1 above with average PSNR value $28{\sim}29[dB]$, do not lossless encoding process using JPEG. And the encoding time is reduced by maximum 11.5 %.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.305-312
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• 1996

A new three dimensional fractal coding is proposed with a perceptually enhanced matching. Since most of medical images (e.g. computed tomoyaphy or magnetic resonance images) have three dimensional characters, searching regions are extended to adjacent slices. For a perceptually enhanced matching, a high frequency boost filter is used for pre-filtering images to be encoded, and a least mean square error matching is applied to the edge enhanced Images rather than the original images. From simulation with magnetic resonance images($255\times255$, 8bits/pixel), reconstructed images by the proposed compression algorithm show much improved subjective image quality with higher peak signnal-to-noise ratio compared to those by existing fractal coding algorithms at compression ratios of about 10.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.19-27
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• 2001

The conventional fractal image compression based on wavelet transform has the disadvantage that the encoding takes many time, since it finds the optimum domain for all the range blocks. In this paper, we propose the fractal image compression based on wavelet transform using the SAS(Self Affine System) techniques. It consists of the range and domain blocks in the wavelet transform, and the range blocks select the domain which is located the relatively same position. In the encoding process, the proposed methods introduce SAS techniques that the searching process of the domains blocks is not required. Therefore, it can perform a fast encoding by reducing the computational complexity. And, the image quality is improved using the different scale factors for each level and the sub-tree in the decoding. As a result, the image quality and the compression ratio are adjustable by the scale factors.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1085-1092
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• 2002

Studies on image information processing have been performed since long time ago because in daily life most of information are acquired by the since of sight. Since there should be a lot of data to describe image as a digital form, data compression is required in order to store or transmit digital image. Lately among most of image compression methods adopted on image compression standards, transform coding methods have been primarily used which transforms the correlations between pixels of image on frequency domain before image compression. It is blown that the standard methods using especially DCT features blocking effect which is the major cause of degrading the quality of image at high compression rate. Fractal encoding using quadtree partition is applied after reducing original image, and we are to find a optimal encoding for the number of scaling bit and offset bit.

• Journal of Industrial Technology
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• v.15
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• pp.93-101
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• 1995

Fractal coding is a promising method for image compression, but it has not lived up to its promise as low bit-rate image compression scheme. The existing algorithms for finding self-mapping contractive transforms are computationally expensive and offer a poor rate-quality tradeoff. In this paper, we propose a segment based fractal coding. We classify the range blocks into shade, midrange or edge blocks, and segment edge block along the edge. And we apply midrange coding scheme for each segment. Our experiments show that our method gives better rate-qualty trade of than current fractal block coding methods.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.589-598
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• 2003

In the conventional fractal image compression in the DWT(discrete wavelet transform), the domain and range blocks were classified as B${\times}$B block size first before all domain block for each range block was searched. The conventional method has a disadvantages that the encoding time takes too long, since the domain block for entire image was searched. As an enhancement to such inefficiencies and image quality, this paper proposes wavelet-based fractal image compression with multiscale factors. Thus, this proposed method uses multiscale factor along each level and band to enhance an overall image quality. In encoding process of this method, the range blocks are not searched for all the domain blocks; however, using the self affine system the range blocks are selected from the blocks in the upper level. The image qualify of the conventional method is 32.30[dB], and the proposed method is 35.97[dB]. The image quality is increased by 3.67[dB].

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.97-102
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• 1998

In this paper, 1 proposed methods of fractal image compression to get better orginal images in a high compression raitos with encoding image effectively. For given signal-to-noise raitos tolerances, show the proposed compression method are higher than Fisher's method for compression raitos at all thresholds. This is due to improve compression time in the local IFS structure that reduce PIFS information storage requirements from 48bits range blocks to the 40bits.