Titlebook: Iterative Identification and Restoration of Images; Reginald L. Lagendijk,Jan Biemond Book 1991 Springer Science+Business Media New York 1

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Maximum Likelihood Image Identification, prior to the restoration process. In many practical situations of interest these parameters are, however, not available. Image identification (sometimes referred to as blur identification, image-blur identification, or a . restoration) focuses on developing estimation procedures, which identify all

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0893-3405 In many instances one has the feeling that the degradations in the image are such that relevant information is close to being recognizable, if only the image could be sharpened just a little. This monograph discusses the two essential steps by which this can be achieved, namely the topics of image i

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The Image Identification and Restoration Problem,remote sensing purposes, blurs are introduced by atmospheric turbulence, aberrations in the optical system, and relative motion between the camera and the ground. Such blurring is not confined to optical images, for example electron micrographs are corrupted by spherical aberrations of the electron lenses and CT scans suffer from X-ray scatter.

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Iterative Image Restoration, regularizing the restoration process. Section4.3 presents a variation on the basic scheme which asymptotically produces the Tikhonov-Miller regularized solution. Finally, Section4.4 is concerned with procedures for increasing the convergence speed of the iterative algorithms.

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