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Introduction to the special issue on image enhancement
Paltern Recognition
Pergamon Press 1970. Vol. 2, pp. 67 68.
Printed in Great Britain
Introduction to the Special Issue on Image Enhancement IN MANYpictorial pattern recognition tasks, the images we have to work with are of poor quality. The prospect of successful recognition would be greatly increased, if we could enhance the image quality. This special issue of Pattern Recognition is meant to introduce to workers in pictorial pattern recognition some of the image enhancement techniques. Although I have been working in the general area of image processing for many years, my interest in image enhancement per se did not begin until the summer of 1966 when I participated in a summer study on image restoration, ~1~sponsored by the National Academy of Sciences. This summer study, under the skilful directorship of Dr. Sam Morgan of the Bell Telephone Laboratories, must be considered as a key event in the history of image enhancement. Many experts in diverse fields gathered together in pleasant Woods Hole and discussed and worked on various aspects of image enhancement. Much of the recent work on image enhancement, in particular almost all of the results reported in the present special issue, are stimulated by this meeting of minds. Another event of note was a seminar on Motion-Degraded Images t2) held at NASA Electronics Research Center, Cambridge, Mass., in December 1968, under the chairmanship of Dr. Max Nagel (NASA/ERC). Anyone interested in finding out the state-of-the-art in image enhancement will do well to look through the proceedings of this seminar. The reader may also want to read my brief review article t3~ to gain a bird's-eye-view of the field of image enhancement. The papers in this special issue on image enhancement fall roughly into two categories. Four of the papers (Harris, Molden, Robbins and Goodman) deal with methodology, the remaining three (Schreiber, Shack and Lee) with implementation. One of the important problems in image enhancement is image restoration. We assume that the degraded image we have at hand was obtained by passing an ideal image through a degrading system whose characteristics we know something about. The problem is to recover (the best we can) the ideal image. If the degrading system is linear and shift-invariant, and if we know its transfer function, then the restoration of the ideal image can in principle be done by a simple division in the spatial frequency domain. Aside from the effect of the ever-present noise, the method will run into trouble if the transfer function of the degrading system is identically zero outside a certain region in the spatial frequency plane, because then the frequency components of the ideal image outside this region cannot be recovered by division. This situation occurs in all optical imaging because of diffraction. Harris, in his paper, discusses techniques (in particular, analytic continuation) for handling this difficult situation, and presents some experimental results. When the ideal image is stationary while the degrading medium is time-varying, one can gain by taking several pictures and using statistical estimation. Such an approach is reported by Moldon. In the papers of Harris and Moldon, and in fact in most works on image restoration, one assumes that the degrading system is linear and shift-invariant. However, many linear degrading systems of practical interest are shift-variant. The general problem of restoring 67
68
Introduction
images degraded by linear shift-variant systems is equivalent to solving linear integral equations (with noise to boot) which is fraught with difficulties. However, Robbins discovered that an important subclass of these systems, which includes the coma aberration of a spherical lens, can be handled by transform techniques. In doing image enhancement work, we should consider not only techniques of improving image quality after the picture has been taken, but also ways of taking pictures such that the image degradation is minimized. Goodman advocates an even more general approach : we should devise optical imaging systems which would give us images suitable for postfacto image enhancement. Examples of such systems (very ingenious) are described in Goodman's paper. The remaining three papers of this special issue concern mainly with implementation. The most commonly used operation in image enhancement is linear (shift-invariant) filtering, which can be done by using digital computer, coherent and incoherent optical systems and special electro-optical devices. Schreiber and Shack, in their respective papers, describe the use of optical scanners in linear filtering. It is indeed refreshing to see how one can achieve significant quality improvement in at least some real-life systems by the employment of simple and practical techniques (Schreiber). Lee discusses various ways of doing linear filtering with optical systems. In particular, he describes several methods (including his own invention) of making optical spatial filters on a digital computer. This collection of papers is only a small sampling of the field of image enhancement. We hope that they will whet the appetite of the reader so that he will dig into the by now rather vast literature on image enhancement and related areas. THOMAS S. HUANG
REFERENCES 1. S. MORGAN(ed.), Restoration of atmospherically-degraded images, Report o f an N A S Summer Study, July 1966, Woods Hole, Mass. 2. M. NAGEL(ed.), Evaluation of motion-degraded images, Proc. o f a Seminar held at NASA/ERC, December 1968, Cambridge, Mass. 3. T. S. HUANG, Image enhancement: A review, Opto-Electronics 1 (1), 49-59 (1969).
Pergamon Press 1970. Vol. 2, pp. 67 68.
Printed in Great Britain
Introduction to the Special Issue on Image Enhancement IN MANYpictorial pattern recognition tasks, the images we have to work with are of poor quality. The prospect of successful recognition would be greatly increased, if we could enhance the image quality. This special issue of Pattern Recognition is meant to introduce to workers in pictorial pattern recognition some of the image enhancement techniques. Although I have been working in the general area of image processing for many years, my interest in image enhancement per se did not begin until the summer of 1966 when I participated in a summer study on image restoration, ~1~sponsored by the National Academy of Sciences. This summer study, under the skilful directorship of Dr. Sam Morgan of the Bell Telephone Laboratories, must be considered as a key event in the history of image enhancement. Many experts in diverse fields gathered together in pleasant Woods Hole and discussed and worked on various aspects of image enhancement. Much of the recent work on image enhancement, in particular almost all of the results reported in the present special issue, are stimulated by this meeting of minds. Another event of note was a seminar on Motion-Degraded Images t2) held at NASA Electronics Research Center, Cambridge, Mass., in December 1968, under the chairmanship of Dr. Max Nagel (NASA/ERC). Anyone interested in finding out the state-of-the-art in image enhancement will do well to look through the proceedings of this seminar. The reader may also want to read my brief review article t3~ to gain a bird's-eye-view of the field of image enhancement. The papers in this special issue on image enhancement fall roughly into two categories. Four of the papers (Harris, Molden, Robbins and Goodman) deal with methodology, the remaining three (Schreiber, Shack and Lee) with implementation. One of the important problems in image enhancement is image restoration. We assume that the degraded image we have at hand was obtained by passing an ideal image through a degrading system whose characteristics we know something about. The problem is to recover (the best we can) the ideal image. If the degrading system is linear and shift-invariant, and if we know its transfer function, then the restoration of the ideal image can in principle be done by a simple division in the spatial frequency domain. Aside from the effect of the ever-present noise, the method will run into trouble if the transfer function of the degrading system is identically zero outside a certain region in the spatial frequency plane, because then the frequency components of the ideal image outside this region cannot be recovered by division. This situation occurs in all optical imaging because of diffraction. Harris, in his paper, discusses techniques (in particular, analytic continuation) for handling this difficult situation, and presents some experimental results. When the ideal image is stationary while the degrading medium is time-varying, one can gain by taking several pictures and using statistical estimation. Such an approach is reported by Moldon. In the papers of Harris and Moldon, and in fact in most works on image restoration, one assumes that the degrading system is linear and shift-invariant. However, many linear degrading systems of practical interest are shift-variant. The general problem of restoring 67
68
Introduction
images degraded by linear shift-variant systems is equivalent to solving linear integral equations (with noise to boot) which is fraught with difficulties. However, Robbins discovered that an important subclass of these systems, which includes the coma aberration of a spherical lens, can be handled by transform techniques. In doing image enhancement work, we should consider not only techniques of improving image quality after the picture has been taken, but also ways of taking pictures such that the image degradation is minimized. Goodman advocates an even more general approach : we should devise optical imaging systems which would give us images suitable for postfacto image enhancement. Examples of such systems (very ingenious) are described in Goodman's paper. The remaining three papers of this special issue concern mainly with implementation. The most commonly used operation in image enhancement is linear (shift-invariant) filtering, which can be done by using digital computer, coherent and incoherent optical systems and special electro-optical devices. Schreiber and Shack, in their respective papers, describe the use of optical scanners in linear filtering. It is indeed refreshing to see how one can achieve significant quality improvement in at least some real-life systems by the employment of simple and practical techniques (Schreiber). Lee discusses various ways of doing linear filtering with optical systems. In particular, he describes several methods (including his own invention) of making optical spatial filters on a digital computer. This collection of papers is only a small sampling of the field of image enhancement. We hope that they will whet the appetite of the reader so that he will dig into the by now rather vast literature on image enhancement and related areas. THOMAS S. HUANG
REFERENCES 1. S. MORGAN(ed.), Restoration of atmospherically-degraded images, Report o f an N A S Summer Study, July 1966, Woods Hole, Mass. 2. M. NAGEL(ed.), Evaluation of motion-degraded images, Proc. o f a Seminar held at NASA/ERC, December 1968, Cambridge, Mass. 3. T. S. HUANG, Image enhancement: A review, Opto-Electronics 1 (1), 49-59 (1969).