Paper
1 November 1991 Image restoration and identification using the EM and adaptive RAP algorithms
Shyh-shiaw Kuo, Richard J. Mammone
Author Affiliations +
Abstract
A new iterative algorithm for image restoration and point spread function (PSF) estimation is presented. The method initially estimates the PSF and the original image using the Expectation Maximization (EM) method. The resulting image estimate is then refined by using the adaptive Row Action Projection (RAP) algorithms which is based on the theory of Projection Onto Convex Sets (POCS). The new implementation of the RAP algorithm can be performed efficiently in parallel and facilitates locally adaptive constraints and cycling strategies. The PSF is re-estimated using a least square technique. Computer simulations illustrate the new method to be very competitive in restoring degraded images and estimating the PSF from noisy blurred images with unknown PSF.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shyh-shiaw Kuo and Richard J. Mammone "Image restoration and identification using the EM and adaptive RAP algorithms", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50312
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KEYWORDS
Point spread functions

Expectation maximization algorithms

Image processing

Image restoration

Autoregressive models

Image analysis

Visual communications

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