• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.57.2-62
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• 1999

Fractal coding is image compression techniques using one of image characteristics self-transformability. In fractal image coding, the encoding process is to select the domain block similar to a range block. The reconstructed image quality of fractal image coding depends on similitude between a range block and the selected domain block. Domain block similar to a range blocks. In fact, the error of the reconstructed image adds up the generated error in encoding process and the generated error in decoding process. But current domain block estimating function considered only the encoding error. We propose a domain block estimating function to consider not only the encoding error but also the decoding error. By computer simulation, it was verified to obtain the high quality reconstructed image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1457-1470
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• 2015

In wireless multimedia sensor networks (WMSN), the latency of transmission is an increasingly problem. With the improvement of resolution, the time cost in image and video compression is more and more, which seriously affects the real-time of WMSN. In JPEG system, the core of the system is DCT, but DCT-JPEG is not the best choice. Block-based DCT transform coding has serious blocking artifacts when the image is highly compressed at low bit rates. APBT is used in this paper to solve that problem, but APBT does not have a fast algorithm. In this paper, we analyze the structure in JPEG and propose a parallel framework to speed up the algorithm of JPEG on GPU. And we use all phase biorthogonal transform (APBT) to replace the discrete cosine transform (DCT) for the better performance of reconstructed image. Therefore, parallel APBT-JPEG is proposed to solve the real-time of WMSN and the blocking artifacts in DCT-JPEG in this paper. We use the CUDA toolkit based on GPU which is released by NVIDIA to design the parallel algorithm of APBT-JPEG. Experimental results show that the maximum speedup ratio of parallel algorithm of APBT-JPEG can reach more than 100 times with a very low version GPU, compared with conventional serial APBT-JPEG. And the reconstructed image using the proposed algorithm has better performance than the DCT-JPEG in terms of objective quality and subjective effect. The proposed parallel algorithm based on GPU of APBT also can be used in image compression, video compression, the edge detection and some other fields of image processing.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.2
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• pp.103-113
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• 2001

This paper described a design and implementation of a single-chip encoder/decoder using the LZSS algorithm and entropy coding in 0.6${\mu}{\textrm}{m}$ CMOS technology. Dictionary storage for the dictionary search processor(DISP) used a 2K$\times$8bit on-chip memory with 50MHz clock speed. It performs compression on byte-oriented input data at a data rate of one byte per clock cycle except when one out of every 33 cycles is used to update the string window of dictionary. In result, the average compression ratio is 46% by applied entropy coding of the LZSS codeword output. This is to improved on the compression performance of 7% much more then LZSS.

• Journal of the Korean Society of Radiology
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• v.8 no.7
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• pp.435-441
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• 2014

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the RGB image compression rate and image quality, such as gray-level images and showed good.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.5
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• pp.390-399
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• 1988

A conventional BTC has the merit of real time processing and simple computation, but has the problem that its compression rate is low. In this paper, a modified BTC using the Quad Tree which is frequently used in binary image is proposed. The method results in the low compression rate by decreasing the total number of subblocks by mean of making the size of a subblock large in the small variation area of graty level and the size af a subblock small in the large variation area of gary level. For the effective transmission of bit plane, the Huffman run-lengh code for the large size of a subblock and the lookup table for tha small size of a subblock are used. The proposed BTC method show the result of coding 256 level image at the average data rate of about 0.8 bit/pixel.

• Journal of the Korean Society of Radiology
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• v.10 no.4
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• pp.263-270
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• 2016

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the YIQ image compression rate and image quality, such as RGB images and showed good.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.5
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• pp.335-344
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• 2003

The image compression based on discrete wavelet transform has been widely accepted in industry since it shows no block artifacts and provides a better image quality when compressed to low bits per pixel, compared to the traditional JPEG. The coefficients generated by discrete wavelet transform are quantized to reduce the number of code bits to represent them. After quantization, lossless coding processes are usually applied to make further reduction. This paper presents a new and efficient lossless coding algorithm for quantified wavelet coefficients based on the statistical properties of the coefficients. Combined with discrete wavelet transform and quantization processes, our algorithm has been implemented as an image compression chip, using 0.5${\mu}{\textrm}{m}$ standard cells. The experimental results show the efficiency and performance of the resulting chip.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.677-690
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• 1995

In this paper, we propose the high efficiency data compression capable of error control using block-sorting, move to front(MTF) and arithmetic code with variable length in to fixed out. First, the substring with is parsed into length N is shifted one by one symbol. The cyclic shifted rows are sorted in lexicographical order. Second, the MTF technique is applied to get the reference of locality in the sorted substring. Then the preprocessed sequence is coded using VF(variable to fixed) arithmetic code which can be limited the error propagation in one codeword. The key point is how to split the fixed length codeword in proportion to symbol probabilities in VF arithmetic code. We develop the new VF arithmetic coding that split completely the codeword set for arbitrary source alphabet. In addition to, an extended representation for symbol probability is designed by using recursive Gray conversion. The performance of proposed method is compared with other well-known source coding methods with respect to entropy, compression ratio and coding times.