Image compression for facial photographs based on wavelet transform

TitleImage compression for facial photographs based on wavelet transform
Publication TypeConference Paper
Year of Publication1997
AuthorsBarzykina, E., P. Nasiopoulos, and R. K. Ward
Conference NameCommunications, Computers and Signal Processing, 1997. '10 Years PACRim 1987-1997 - Networking the Pacific Rim'. 1997 IEEE Pacific Rim Conference on
Pagination322 -325 vol.1
Date Publishedaug.
Keywordscompression rates, data compression, discrete wavelet transform, entropy codes, entropy encoding, face recognition, facial features, facial image databases, facial photographs, feature extraction, frequency dependent quantization, frequency distribution, identification, image coding, image compression algorithm, image segmentation, input image, memory requirements reduction, quantisation (signal), space dependent quantization, spacial areas detection, spatial content, transforms, visual quality, wavelet coefficients, wavelet transforms

This paper presents a wavelet based image compression algorithm specifically tailored for facial photographs. The proposed method dramatically reduces memory requirements for facial image databases. The algorithm makes it possible to reach compression rates of 0.25 to 0.1 bpp without compromising the visual quality of the facial features used for identification purposes. This is made possible by utilizing a novel strategy for quantizing the wavelet coefficients, where the spatial content and the frequency distribution of each input image are combined to produce a quantization scheme which is spatially and frequency dependent and different for each image being processed. The main steps of the algorithm are as follows: detection of more and less important spacial areas in the photograph; discrete wavelet transform; space and frequency dependent quantization customized for a specific frequency distribution of each image; and entropy encoding


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