Paper
17 November 2000 Construction of compactly supported biorthogonal wavelet based on Human Visual System
Haiping Hu, Weidong Hou, Hong Liu, Yu Long Mo
Author Affiliations +
Abstract
As an important analysis tool, wavelet transform has made a great development in image compression coding, since Daubechies constructed a kind of compact support orthogonal wavelet and Mallat presented a fast pyramid algorithm for wavelet decomposition and reconstruction. In order to raise the compression ratio and improve the visual quality of reconstruction, it becomes very important to find a wavelet basis that fits the human visual system (HVS). Marr wavelet, as it is known, is a kind of wavelet, so it is not suitable for implementation of image compression coding. In this paper, a new method is provided to construct a kind of compactly supported biorthogonal wavelet based on human visual system, we employ the genetic algorithm to construct compactly supported biorthogonal wavelet that can approximate the modulation transform function for HVS. The novel constructed wavelet is applied to image compression coding in our experiments. The experimental results indicate that the visual quality of reconstruction with the new kind of wavelet is equivalent to other compactly biorthogonal wavelets in the condition of the same bit rate. It has good performance of reconstruction, especially used in texture image compression coding.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haiping Hu, Weidong Hou, Hong Liu, and Yu Long Mo "Construction of compactly supported biorthogonal wavelet based on Human Visual System", Proc. SPIE 4122, Mathematics and Applications of Data/Image Coding, Compression, and Encryption III, (17 November 2000); https://doi.org/10.1117/12.409248
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Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Image compression

Visual system

Wavelet transforms

Algorithm development

Modulation transfer functions

Discrete wavelet transforms

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