• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.496-512
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• 2007

In this paper, we propose a novel JPEG-2000 compressed image retrieval system using feature vector extracted through partial entropy decoding. Main idea of the proposed method is to utilize the context information that is generated during entropy encoding/decoding. In the framework of JPEG-2000, the context of a current coefficient is determined depending on the pattern of the significance and/or the sign of its neighbors in three bit-plane coding passes and four coding modes. The contexts provide a model for estimating the probability of each symbol to be coded. And they can efficiently describe texture images which have different pattern because they represent the local property of images. In addition, our system can directly search the images in the JPEG-2000 compressed domain without full decompression. Therefore, our proposed scheme can accelerate the work of retrieving images. We create various distortion and similarity image databases using MIT VisTex texture images for simulation. we evaluate the proposed algorithm comparing with the previous ones. Through simulations, we demonstrate that our method achieves good performance in terms of the retrieval accuracy as well as the computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.64-71
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• 2003

In this paper, we proposed an algorithm that shorten coding time maintaining image quality in JPEG2000, which is the standard, of still image compression. This method encodes only the bit plane selected as appropriate truncation point for output bitstream, obtained from estimation of frequency distribution for whole image. Wavelet characterized by multi-resolution has vertical, horizontal, and diagonal frequency components for each resolution. The frequency interrelation addressed above is maintained thorough whole level of resolution and represents the unique frequency characteristics for input image. Thus, using the frequency relation at highest level, we can pick the truncation point for the compression time decrease by estimating code bits at encoding each code block. Also, we reduced the encoding time using simply down sampling instead of low-pass filtering at low-levels which are not encoded in color component of lower energy than luminance component. From the proposed algorithm, we can reduce about 15~36% of encoding time maintaining PSNR 30$\pm$0.5㏈.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.635-646
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• 2011

In distributed video coding, low complexity encoder can be realized by shifting encoder-side complex processes to decoder-side. However, not only motion estimation/compensation processes but also complex LDPC decoding process are imposed to the Wyner-Ziv decoder, therefore decoder-side complexity has been one important issue to improve. LDPC decoding process consists of numerous iterative decoding processes, therefore complexity increases as the number of iteration increases. This iterative LDPC decoding process accounts for more than 60% of whole WZ decoding complexity, therefore it can be said to be a main target for complexity reduction. Previously, HDA (Hard Decision Aided) method is introduced for fast LDPC decoding process. For currently received parity bits, HDA method certainly reduces the complexity of decoding process, however, LDPC decoding process is still performed even with insufficient amount of parity request which cannot lead to successful LDPC decoding. Therefore, we can further reduce complexity by avoiding the decoding process for insufficient parity bits. In this paper, therefore, a parity request estimation method is proposed using bit plane-wise correlation and temporal correlation. Joint usage of HDA method and the proposed method achieves about 72% of complexity reduction in LDPC decoding process, while rate distortion performance is degraded only by -0.0275 dB in BDPSNR.