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For example, this representation can be used to denoise the image because, from this representation, one can compute the Lipschitz exponents and by putting a threshold on the exponents, remove white noise from a noisy image. Therefore, one can suggest to use this representation either for purposes other than image compression, or within another coding scheme. This representation can be very useful in pattern recognition algorithms or classification because it extracts important image structure, and classification is often performed using this type of information.

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22] A. Singh and V. Bove, Image Quality Measure Based on a Human Visual System Model, IEEE Journal on Selected Areas in Communications, Vol 11, No 1, Jan 1993. [23] J. Kim, H. Lee and J. Choi, Subband Coding Using Human Visual Characteristics for Image Signals, IEEE Journal on Selected Areas in Communications, Vol 11, No 1, Jan 93. [24] G. Karlsson and M. Vetterli, Three Dimensional Subband Coding of Video, Proceedings of IEEE ICASSP, 1988, pp. 1100-1103. [25] M. Perkins and T. Lookabaugh A Psychophysically Justified Bit Allocation Algorithm for Subband Image Coding Systems, Proceedings of IEEE ICASSP 1989.

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