@inproceedings{9eee37a3400047fc8dea192b017ee7c8,
title = "Fundamental equivalences between set-Theoretic & maximum-entropy methods in multiple-domain image restoration",
abstract = "Several powerful, but heuristic techniques in the image denoising literature have used overcomplete image representations. A general framework for incorporating information from multiple representations based on fundamental statistical estimation principles was presented in Ishwar and Moulin (1999) where, information about image attributes from multiple wavelet transforms was incorporated as moment constraints on the underlying image prior. In this paper we explore the fundamental equivalence between the stochastic setting of multiple-domain restoration in Ishwar and Moulin and its deterministic set-Theoretic counterpart. The main technical tool is the Lagrange multiplier theory of constrained optimization. The insights gained by this analysis allow us to derive a state-of-The-Art denoising algorithm.",
author = "Prakash Ishwar and Pierre Moulin",
year = "2000",
doi = "10.1109/ICASSP.2000.861899",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "161--164",
booktitle = "Signal Processing Theory and Methods I",
address = "United States",
note = "25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 ; Conference date: 05-06-2000 Through 09-06-2000",
}