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2008

Maximum-Entropy Expectation-Maximization Algorithm for Image Reconstruction and Sensor Field Estimation

13 years 12 months ago
Maximum-Entropy Expectation-Maximization Algorithm for Image Reconstruction and Sensor Field Estimation
Abstract--In this paper, we propose a maximum-entropy expectation-maximization (MEEM) algorithm. We use the proposed algorithm for density estimation. The maximum-entropy constraint is imposed for smoothness of the estimated density function. The derivation of the MEEM algorithm requires determination of the covariance matrix in the framework of the maximum-entropy likelihood function, which is difficult to solve analytically. We, therefore, derive the MEEM algorithm by optimizing a lower-bound of the maximum-entropy likelihood function. We note that the classical expectation-maximization (EM) algorithm has been employed previously for 2-D density estimation. We propose to extend the use of the classical EM algorithm for image recovery from randomly sampled data and sensor field estimation from randomly scattered sensor networks. We further propose to use our approach in density estimation, image recovery and sensor field estimation. Computer simulation experiments are used to demonstr...
Hunsop Hong, Dan Schonfeld
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TIP
Authors Hunsop Hong, Dan Schonfeld
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