• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.20-25
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• 2016

This study addresses a low complexity and lossless frame memory compression algorithm based on block-buffer structure for efficient high resolution video processing. Our study utilizes the block-based MHT (modified Hadamard transform) for spatial decorrelation and AGR (adaptive Golomb-Rice) coding as an entropy encoding stage to achieve lossless image compression with low complexity and efficient hardware implementation. The MHT contains only adders and 1-bit shift operators. As a result of AGR not requiring additional memory space and memory access operations, AGR is effective for low complexity development. Comprehensive experiments and computational complexity analysis demonstrate that the proposed algorithm accomplishes superior compression performance relative to existing methods, and can be applied to hardware devices without image quality degradation as well as negligible modification of the existing codec structure. Moreover, the proposed method does not require the memory access operation, and thus it can reduce costs for hardware implementation and can be useful for processing high resolution video over Full HD.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.102-107
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• 2000

In general text compression techniques cannot be used directly in image compression because the model of text and image are different Recently, a new class of text compression, namely, block-sorting algorithm which involves Burrows and Wheeler transformation(BWT) gives excellent results in text compression. However, if we apply it directly into image compression, the result is poor. So, we propose simple method in order to improve the lossless compression performance of image. The proposed method can be divided into three steps. It is decomposed into ten subbands with the help of symmetric short kernel filter. The resulting subbands are block-sorted according to the method by BWT, and the redundancy is removed with the help of an adaptive arithmetic coder. Experimental results show that the proposed method is better than lossless JPEG and LZ-based compression method(PKZIP).

• Journal of Broadcast Engineering
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• v.11 no.2 s.31
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• pp.153-163
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• 2006

We propose a new video compression method based on MCTF(motion compensated temporal filtering) with constant quality. SPECK is an efficient image compression coding method of encoding DWT coefficients. Especially SPECK method is very efficient for coding the motion compensated residual image which usually has larger amounts of high frequency components than the natural images. And proposed multi block size hierarchical motion estimation technique is more efficient than classical block matching algorithm with fixed block size both in estimation precision and operation costs. Proposed video method based on MCTF video compression can also support multi-frame rate decoding with reasonable complexity. Simulation results showed that proposed method outperforms H.263 video compression standard.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.915-927
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• 1997

In this paper, we propose an error concealment technique using directional interpolation in block-based image compression. In the proposed method the edge direction is determined by finding the maximum correlation coefficients of boundary pixels of blocks neighboring the errored block in spatial domain. Then the errored block is interpolated linearly or bilinearly along the determined edge direction. The proposed method can conceal the block error, the macro block error, and the slice error adaptively. Also, the parameters for the directional interpolation are represented by closed forms. When applied to compressed images, the proposed method shows superior subjective and objective quality to conventional error concealment methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.180-181
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• 2018

JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the array of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform).

• 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.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1787-1790
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• 2003

In this paper. we proposed a hardware(H/W) structure which can compress the video and embed the watermark in real time operation and implemented it into a FPGA platform using VHDL(VHSIC Hardware Description Language). All the image processing element to process both compression and reconstruction in a FPGA were considered each of them was mapped into H/W with the efficient structure for FPGA. The global operations of the designed H/W consists of the image compression with the watermarking and the reconstruction, and the watermarking operation is concurrently operated with the image compression. The implemented H/W used the 59％(12943) LAB(Logic Array Block) and 9％(28352) ESB(Embedded System Block) in the APEX20KC EP20K600CB652-7 FPGA chip of ALTERA, and stably operated in the 70㎒ clock frequency over. So we verified the real time operation, 60 fields/sec(30 frames/sec).

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.38-41
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• 1993

For efficient transmission and storage of digital images, the requirements of image compression is incresing. Because the medical images contain diagnostic information small distortion has been more important factor than the low rate in such images. Generally the distortion in image is the difference of pixel values. However the image is percieved by human visual systems. So it is reasonable that human visual system characteristics be used as criteria of the image compression. In this paper, the Just Noticeable Difference curve is used as criteria of determining the homogeniety of a block and acceptibility of distortions. And Block Truncation Coding using spatial masking effect of eyes is adopted to code the blocks which contain line components. And small blocks which varies slowly can be approximated to polynomial functions successfully. We proposed the hybrid block coding scheme based on the block characteristics and human visual system characteristics. Simulation to several kinds of the medical images using this method showed that medical images can be compressed 5:1 - 10:1 without noticeable distortion.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.67-74
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• 2015

BTC (Block Truncation Coding) image compression is simple to implement by hardware and has excellent edge retention capability of image, image compression techniques are widely used in LCD overdrive. In this paper, to maintain high visual quality and has high compression rate, Multi-Mode BTC (MM-BTC) algorithm is proposed. The MM-BTC has high compression rate using advanced Y-based BTC method and has high visual quality using improved 2-level and 4-level BTC method in this paper. As shown in simulation results, MM-BTC improves still image PSNR (Peak Signal to Noise Ratio) up to 2.34 dB as compared with other algorithms. When the MM-BTC is applied to LCD overdrive, MM-BTC improves moving picture PSNR up to 2.33 dB as compared with other algorithms in literature.