Paper
28 December 1998 Two-dimensional optimum band partition based on band blocks for subband image coding
Masashi Kameda, Kohhei Ohtake, Makoto M. Miyahara
Author Affiliations +
Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998) https://doi.org/10.1117/12.334612
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
Subband coding is important (1) to decompose an input signal into an adequate set of subbands considering the property of an input signal and (2) to assign an adequate bits in proportion with the power of each subband signal. Investigation of auto-correlation characteristics of several kinds of images reveals us an isotropic correlation model. Based on this theoretical image model, we have derived the optimum band partition that minimizes the quantization noise power of the reconstructed signal at the receiving end. In order to apply the above theoretical optimum band partition to the image coding, we propose the optimum band partition scheme based on an idea of a set of band blocks, and we present the calculation algorithm with the low computational complexity to determine the optimum band partition. Also, we propose two methods to exploit the non-stationary nature of images, and the filter bank configuration to realize the optimum band partition including these methods. The proposed optimum band partition shows better result than that of the blocking DCT in obtaining the higher compression rate and the higher image quality.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Masashi Kameda, Kohhei Ohtake, and Makoto M. Miyahara "Two-dimensional optimum band partition based on band blocks for subband image coding", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); https://doi.org/10.1117/12.334612
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KEYWORDS
Image compression

Quantization

Image filtering

Image quality

Electronic filtering

Interference (communication)

Digital filtering

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