• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.938-946
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• 1996

Hierarchical subband codec has been widely promoted in the field of data compression/decompression because of their simplicity and modular nature. Over the past years, the study has received great attention to the perfect reconstruction (PR)system which perfectly recovers the original input signal at the reconstructed output. However, in the actual subband codec system, the signals that passed through the analysis filter bank are quantized before transmission to the receiver side and reconstructed by the synthesis filter bank. Thus the PR system is impossible and the quantization effects must be carefully considered in the system design such that the system recovers the reconstructed output as possible to the the original input signal with minimum quantization error.In this paper, we propose an optimum hierarchical subband codec structure in the presence of quantizer. The optimality criteria of the code is given to the deign of the hierarchical analysis/synthesis subband filter bank and the quantizer that minimize then output mean square error due to the quantizer in the codec. Specific opti-mum design esamples are shown with level-1, level-2 hierarchical structure. The optimal designs are verified by computer simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.129-138
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• 2013

This paper is a study on Dual Tree Complex Wavelet Transform, which improved directional information for efficient image processing. Dual Tree Complex Wavelet Transform satisfies characteristics of shift invariance, and includes 6 directional information, which is more than previous Discrete Wavelet Transform. However, in images of buildings, there are many horizontal and vertical edge components. Therefore, all the high-frequency components of image are not expressed by 6 directional information subbands. This paper proposes 8-directional Complex Wavelet Transform with excellent high-frequency separation features by creating horizontal vertical($0^{\circ}$, $90^{\circ}$) subband besides 6 directional information subband of previous Dual Tree Complex Wavelet Transform. The proposed method can create and combine various directional information subbands according to features of image. Performance is evaluated by applying the method to noise removal.