• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.246-256
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• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.1240-1243
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• 2004

Multi-Valued Image Entropy Coding (MVIEC) is a new class of joint source channel coding, which reduces both input-width (1/4) and average current (0.36-1.3) for LCD source drivers. This paper describes the detail results on MVIEC for several image sets in order to verify the practical performance.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.112-119
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• 1997

Zerotreeimage coding is known as a simple and effective image comprssion algorithm. It has the property that the compression is generated in order of improtance. Conventionally, a fixed threshold is applied to the entire wavelet coefficients regardless of frequency and local features of an image. In this paper, we propose a new zerotree coding scheme with adaptive threshold. The adaptive threshold is determined by human visual characteristics. It is shown that the image quality of the proposed method is better than that of the conventional method.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.609-612
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• 1999

In this paper, we propose wavelet transform image compression method such that an image is decomposed into multiresolutions using biorthogonal wavelet transform with linear phase response property and decomposed subbands are classified by maximum classification gain. The classified data is quantized by allocating bits in accordance with classified class informations within subbands through arbitrary set bit allocation algorithm. And then, quantized data in each subband are entropy coded. The proposed coding method is that the quantized data perform shuffling before entropy coding in order to remove sign bit plane. And the context is assigned by maximum correlation direction for bit plane coding.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.41-44
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• 2002

In the communications systems with diversity, we are commonly faced on needing of new source coding technique, error resilient coding. The error resilient coding addresses the coding algorithm that has the robustness to unreliability of communications channel. In recent years, many error resilient coding techniques were proposed such as data partitioning, resynchronization, error detection, concealment, reference picture selection and multiple description coding (MDC). In this paper, we proposed an MDC using whitening transform. The conventional MDC using correlating transform is need additional information to decode the image. But, if an image is transformed using the whitening transform, the additional information is not necessary to transform because the coefficients of whitening transform have uni-variance statistics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1691-1697
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• 1997

This paper presents a new motion compensated error coding method suitable for region based image coding system. Compared with block based conding, the region based coding improves subjective quality as it estimates and compensates 2D (or 3D) translantional, rotational, and scaling motion for each regions. although the region based coding has this advantage, its merit is reduced as bock-DCT (2D-DCT) is used to encode motion-compensated error. To overcome this problem, a new region adaptive motion compensated error coding technique which improver subjective and objective quality in the region boundary is proposed in this paper. In the proposed method, regions with large error are estimated using contour of the regions and contrast between the regions. The regions estiated as those with large error are coded by arbitrarily shaped image segment coding method. The mask information of the coded regions is not transmitted because it is estimated as the same algorithm in the encoder and the decoder. The proposed region adaptive motion conpensated error coding method improves about 0.5dB when it is compared with conventional block based method.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.149-152
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• 2004

A new joint source channel coding reduces both input-width and average current consumption to transmit image data to LCD source drivers. As a source coding, it is based on entropy coding of differential pulse code modulation scheme, especially using median edge detector of image predictor. As a channel coding, it is not a simple pulse amplitude modulation, but linked by source entropy to reduce average amplitude. Simulation results show 1/4 width is achievable by 16-valued transmission with keeping conventional current consumption (0.36 to 1.3).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2325-2332
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• 1998

In this paper, the quality scalable coding of selected region is presented. If a region is semantically more important than the others, it is appropriate that the image compression shcem is capable of handling the regional semantic difference because the information loss of the region of interest is more severe. We propose the quality scalable coding with its model by interoducing the quality scale parameter. It is more extended and generalized image compression philosophy than te conventional coding. As an implementation of the proposed quality scalable coding, H.263 based scheme is presented. This scheme can control the temporal and spatial quality efficiently, and improve the reconstructed image quality of the region of interest.

• Journal of Digital Contents Society
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• v.7 no.3
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• pp.183-191
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• 2006

Currently, the preferred processing of a user-centered ROI(Region-of-Interest) or a specific region of image to transmission and decompression of a full image is needed in different applications, specifically mobile applications. Here, we have to study how different factors affect ROI coding methods. Therefore, an application can select an ROI coding method and several parameters suitable for the environments. The ROI coding methods used in the study are Maxshift and Implicit and the parameters are tile size, image size, code block size, ROI importance and the number of lowest resolution levels. This study shows the experimental results between the different parameters and the two ROI coding methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.97.1-102
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• 1999

This paper porposes and efficient coding scheme for remote medical communication systems, or“telemedicine systems”. These systems require a technique which is able to transfer large volume of data such as X-ray images effectively. We have already developed a hierarchical image coding and transmission scheme (HITS), which achieves an efficient transmission of medical images simply[1]. In this paper, a new coding scheme for HITS is proposed, which used hierarchical context modeling for the purpose of improving the coding efficiency. The hierarchical context modeling divides wavelet coefficients into several sets by the value of a correspondent coefficient in their higher class, or“a parent”, optimizes a Golomb-Rice (GR) code parameter in each set, and then encodes the coefficients with the parameter. Computer simulation shows that the proposed scheme is effective with simple implementation. This is due to fact that a wavelet coefficient has dependence on its parent. As a result, high speed data transmission is achieved even if the telemedicine system consists of simple personal computers.