• Korean Journal of Digital Imaging in Medicine
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• v.4 no.1
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• pp.166-180
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• 1998

$\cdot$ 영상 압축은 영상의 통계학적 분포, 반복성을 이용하여 빈도가 높은 데이터는 적은 수의 bits를, 빈도가 낮은 데이터에는 보다 많은 수의 bits를 할당하여 전체 영상을 나타내는 bits 수를 줄이는 것임. $\cdot$ 영상 압축은 크게 Lossy Coding, Lossless Coding으로 나뉘며, Lossy coding은 DCT, 양자화기, VLC Codes를 쓰며 압축 율은 높으나 원래의 영상을 정확히 복원하지 못함. $\cdot$ 영상 압축에 대한 국제 규격 협회는 JPEG, MPEG I, MPEG II, MPEG IV, H.261, H.263 등이 있으나 본 seminar에서는 JPEG 규격만 논함. $\cdot$ 의학 영상은 Resolution이 크고 study 단위로 관리되기 때문에 영상 데이터량이 많으나 진단의 목적으로 쓰이기 때문에 주로 lossless 압축을 쓰게 되나 압축율이 낮음.(3:1 이하). 최근에는 Fractal, Wavelet Coding을 통한 압축율을 증가 시키는 Image Compression Algorithms이 활용됨. $\cdot$ MPEG은 동영상의 압축 표준안이며, 동영상은 한frame 당 25개 이상의 정지 화상으로 이루어지기 때문에 JPEG 규격에서 사용되었던 기법이 그대로 활용되며 영상과 영상간, 또는 frame과 frame 간의 여상의 변화, 움직임을 Vector로 coding하는 interframe Coding 기법을 활용하나 설명하기에는 광범위한 topic이므로 본 seminar에서는 생략함.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.35-41
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• 2020

This paper proposes an algorithm to improve the compression performance of the adaptive multi-rate (AMR) speech coding using the context tree weighting (CTW) method. AMR is the voice encoding standard adopted by IMT-2000, and supports 8 transmission rates from 4.75 kbit/s to 12.2 kbit/s to cope with changes in the channel condition. CTW as a kind of the arithmetic coding, uses a variable-order Markov model. Considering that CTW operates bit by bit, we propose an algorithm that re-orders AMR data and compresses them with CTW. To verify the validity of the proposed algorithm, an experiment is conducted to compare the proposed algorithm with existing compression methods including ZIP in terms of compression ratio. Experimental results indicate that the average additional compression rate in AMR data is about 3.21% with ZIP and about 9.10% with the proposed algorithm. Thus our algorithm improves the compression performance of AMR data by about 5.89%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.77-83
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• 2015

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.125-131
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• 1989

This paper proposes a new ABTC (Adaptive Block Truncation Coding) algorithm which improves the BTC algorithm for image data compression. A new adaptive block truncation coding which adopts a selective coding scheme depending on the local characteristics of an image has been described. The characteristics of the ABTC algorithm can be summarized as high compression ratio and the algorithm simplicity. Using this algorithm, color images can be coded at a variable bit rate from 1.0 (bit/pel) to 2.56 (bit/pel) and high compression rate (1.3-105 bit/pel) can be achieved without conspicuous image degradation compared with original images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1296-1302
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• 2009

We propose an efficient coding method of digital holograms using MCTF and standard compression tools for video. The hologram is generated by a computer-generated hologram (CGH) algorithm with both an object image and its depth information. The proposed coding consists of localization by segmenting a hologram, frequency transform using $64\times64$ segment size, 2-D discrete cosine transform DCT for extracting redundancy, motion compensated temporal filtering (MCTF), segment scanning the segmented hologram to form a video sequence, and video coding, which uses H.264/AVC. The proposed algorithm illustrates that it has better properties for reconstruction, 10% higher compression rate than previous research in case of object.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1375-1378
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• 1987

In this paper, an efficient data compression algorithm for binary image is proposed. This algorithm makes use of the fact that boundaries contain all the information about such images. The compression efficiency is then further increased by efficient coding of Boundary Information Matrix. The comparison of performance with modified Huffman coding was made by a computer simulation with some images. The results of simulation showed that the proposed algorithm was more efficient than modified Huffman code.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.355-360
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• 2011

In this paper, we propose a new context-based adaptive binary arithmetic coding (CABAC) method for lossless image compression. Since the conventional CABAC in H.264/AVC was originally designed for lossy coding, it does not yield adequate performance during lossless coding. Therefore, we proposed an improved CABAC method for lossless intra coding by considering the statistical characteristics of residual data in lossless intra coding. Experimental results showed that the proposed method reduced the bit rate by 18.2%, compared to the conventional CABAC for lossless intra coding.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.22-30
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• 2024

Image compression-decompression methods have become increasingly crucial in modern times, facilitating the transfer of high-quality images while minimizing file size and internet traffic. Historically, early image compression relied on rudimentary codecs, aiming to compress and decompress data with minimal loss of image quality. Recently, a novel compression framework leveraging colorization techniques has emerged. These methods, originally developed for infusing grayscale images with color, have found application in image compression, leading to colorization-based coding. Within this framework, the encoder plays a crucial role in automatically extracting representative pixels-referred to as color seeds-and transmitting them to the decoder. The decoder, utilizing colorization methods, reconstructs color information for the remaining pixels based on the transmitted data. In this paper, we propose a novel approach to image compression, wherein we decompose the compression task into grayscale image compression and colorization tasks. Unlike conventional colorization-based coding, our method focuses on the colorization process rather than the extraction of color seeds. Moreover, we employ the Denoising Diffusion Null-Space Model (DDNM) for colorization, ensuring high-quality color restoration and contributing to superior compression rates. Experimental results demonstrate that our method achieves higher-quality decompressed images compared to standard JPEG and JPEG2000 compression schemes, particularly in high compression rate scenarios.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1121-1131
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• 1997

In video coding at high compression rate, factal compression schemes in spatial domain have outstanding blocking artifacts and compression schemes in wavelet transform domain have rinfing artifacts at edges. In order to compensate these disadvantages, we propose a fractal video coding in wavelet transrorm domain which leads to clear edges without blocking atrifacts even at high bompression rate. The proposed method performs variable block sized motion estimation by using correlation among different subbands. Then the wavelet coefficients which are not enoded dffectively by the motion estimation are compressed by inter-frame fractal coding which predicts fine scale subbands hierarchically from the next coarser scale subbands. Computer sumulations with sev-eral test images wequences show that the proposed method shows better performance than the conventional video coding methods using fractal and wavelet.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.687-695
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• 2003

In this paper, we present a document image compression system based on segmentation, Quincunx downsampling, (5/3) wavelet lifting and subband-oriented SPIHT coding. We reduced the coding time by the adaptation of subband-oriented SPIHT coding and Quincunx downsampling. And to increase compression rate further, we applied arithmetic coding to the bitstream of SPIHT coding output. Finally, we present the reconstructed images for visual comparison and also present the compression rates and PSNR values under various scalar quantization methods.