Abstract

The evaluation of an image must depend upon the purpose for which the image was obtained and the manner in which the image is to be examined. Where the goal is extraction of information and where the image is to be processed prior to viewing, the information content of the image is the only true evaluation criterion. Under these conditions, the improvement achieved by processing can be evaluated by comparing the ability of the human observer to extract information from the image before and after processing. The extent to which the processing approaches the optimum can be evaluated by determining the fraction of the total information content of the image which can be visually extracted after processing. The basic mathematical concepts of image processing are indicated, relating the input point spread function (p. s. f. of the unprocessed image), the processing point spread function (p. s. f. which defines the processing operation), and the output point spread function (p. s. f. of the processed image), and their Fourier domain equivalents. Examples are shown of images which have been processed and the details of the processing operations are described.

© 1966 Optical Society of America

Object Restoration in a Diffraction-Limited Imaging System*

Casper W. Barnes
J. Opt. Soc. Am. 56(5) 575-578 (1966)

Iterative image restoration considering visibility

Yoshiki Ichioka and Nobuyoshi Nakajima
J. Opt. Soc. Am. 71(8) 983-988 (1981)

Image Evaluation by Use of the Sampling Theorem*

B. Roy Frieden
J. Opt. Soc. Am. 56(10) 1355-1362 (1966)

Restoration of Turbulence-Degraded Images*

Benjamin L. McGlamery
J. Opt. Soc. Am. 57(3) 293-297 (1967)

Digital Image Restoration by Constrained Deconvolution

David Pearce MacAdam
J. Opt. Soc. Am. 60(12) 1617-1627 (1970)