Multiplicative multiscale image decompositions: analysis and modeling

Justin K. Romberg; Rudolf H. Riedi; Hyeokho Choi; Richard G. Baraniuk

doi:10.1117/12.408660

4 December 2000 Multiplicative multiscale image decompositions: analysis and modeling

Justin K. Romberg, Rudolf H. Riedi, Hyeokho Choi, Richard G. Baraniuk

Proceedings Volume 4119, Wavelet Applications in Signal and Image Processing VIII; (2000) https://doi.org/10.1117/12.408660
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Multiscale processing, in particular using the wavelet transform, has emerged as an incredibly effective paradigm for signal processing and analysis. In this paper, we discuss a close relative of the Haar wavelet transform, the multiscale multiplicative decomposition. While the Haar transform captures the differences between signal approximations at different scales, the multiplicative decomposition captures their ratio. The multiplicative decomposition has many of the properties that have made wavelets so successful. Most notably, the multipliers are a sparse representative for smooth signals, they have a dependency structure similar to wavelet coefficients, and they can be calculated efficiently. The multiplicative decomposition is also a more natural signal representation than the wavelet transform for some problems. For example, it is extremely easy to incorporate positivity constraints into multiplier domain processing. In addition, there is a close relationship between the multiplicative decomposition and the Poisson process; a fact that has been exploited in the field of photon-limited imaging. In this paper, we will show that the multiplicative decomposition is also closely tied with the Kullback-Leibler distance between two signals. This allows us to derive an n-term KL approximation scheme using the multiplicative decomposition.

Citation Download Citation

Justin K. Romberg, Rudolf H. Riedi, Hyeokho Choi, and Richard G. Baraniuk "Multiplicative multiscale image decompositions: analysis and modeling", Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); https://doi.org/10.1117/12.408660

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