One of the most intriguing questions in image processing is the problem of recovering the desired or perfect image from a degraded version. 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 identification and restoration. More specifically the goal of image identifi cation is to estimate the properties of the imperfect imaging system (blur) from the observed degraded image, together with some (statistical) char acteristics of the noise and the original (uncorrupted) image. On the basis of these properties the image restoration process computes an estimate of the original image. Although there are many textbooks addressing the image identification and restoration problem in a general image processing setting, there are hardly any texts which give an indepth treatment of the state-of-the-art in this field. This monograph discusses iterative procedures for identifying and restoring images which have been degraded by a linear spatially invari ant blur and additive white observation noise. As opposed to non-iterative methods, iterative schemes are able to solve the image restoration problem when formulated as a constrained and spatially variant optimization prob In this way restoration results can be obtained which outperform the lem. results of conventional restoration filters."

The range of applications in the area of motion analysis and image sequence processing is expanding with the steady increase in the use of video and television systems in a variety of different fields. A consequence of this expansion is the increased interest in research in this area. Motion Analysis and Image Sequence Processing brings together the fundamentals of various aspects of image sequence processing, as well as the most recent developments and applications. An image sequence is a series of two-dimensional images that are sequentially ordered in time. The analysis of image motion, and processing of image sequences using the motion information is becoming more and more important as video and television systems are finding an increasing number of applications in the areas of entertainment, robot vision, education, personal communications, multimedia, and scientific research. The importance of motion analysis and image sequence processing is due to two major factors. First, the information that needs to be obtained from the sequence may be inherently time-dependent. In that case, spatial information that can be obtained from a single image frame may not bear any useful information, and hence one must utilize temporal information by considering a sequence of images. Second, in some applications it may be advantageous to consider the processing of a sequence of images instead of individual images. This is because one can utilize the naturally existing temporal relationship among the frames of an image sequence to obtain results that are superior to those obtained by frame-by-frame processing of the sequence. Motion Analysis and Image Sequence Processing contains a coherent and rigorous discussion of recent fundamental developments, as well as applications of motion estimation and image sequence processing. Motion Analysis and Image Sequence Processing is a useful reference for engineers, industrial and academic research scientists, graduate students and faculty who are either already active in research in the field or planning to pursue research in one or more aspects of image sequence processing. This book can be used as the textbook in an advanced level course and as a reference. (ABSTRACT) The range of applications in the area of motion analysis and image sequence processing is expanding with the steady increase in the use of video and television systems in a variety of different fields. A consequence of this expansion is the increased interest in research in this area. Motion Analysis and Image Sequence Processing brings together the fundamentals of various aspects of image sequence processing, as well as the most recent developments and applications. An image sequence is a series of two-dimensional images that are sequentially ordered in time. The analysis of image motion, and processing of image sequences using the motion information is becoming more and more important as video and television systems are finding an increasing number of applications in the areas of entertainment, robot vision, education, personal communications, multimedia, and scientific research. The importance of motion analysis and image sequence processing is due to two major factors. First, the information that needs to be obtained from the sequence may be inherently time-dependent. Motion Analysis and Image Sequence Processing contains a coherent and rigorous discussion of recent fundamental developments, as well as applications of motion estimation and image sequence processing. Motion Analysis and Image Sequence Processing is a useful reference for engineers, industrial and academic research scientists, graduate students and faculty who are either already active in research in the field or planning to pursue research in one or more aspects of image sequence processing. This book can be used as the textbook in an advanced level course and as a reference.

An image or video sequence is a series of two-dimensional (2-D) images sequen tially ordered in time. Image sequences can be acquired, for instance, by video, motion picture, X-ray, or acoustic cameras, or they can be synthetically gen erated by sequentially ordering 2-D still images as in computer graphics and animation. The use of image sequences in areas such as entertainment, visual communications, multimedia, education, medicine, surveillance, remote control, and scientific research is constantly growing as the use of television and video systems are becoming more and more common. The boosted interest in digital video for both consumer and professional products, along with the availability of fast processors and memory at reasonable costs, has been a major driving force behind this growth. Before we elaborate on the two major terms that appear in the title of this book, namely motion analysis and image sequence processing, we like to place them in their proper contexts within the range of possible operations that involve image sequences. In this book, we choose to classify these operations into three major categories, namely (i) image sequence processing, (ii) image sequence analysis, and (iii) visualization. The interrelationship among these three categories is pictorially described in Figure 1 below in the form of an "image sequence triangle.""

One of the most intriguing questions in image processing is the problem of recovering the desired or perfect image from a degraded version. 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 identification and restoration. More specifically the goal of image identifi cation is to estimate the properties of the imperfect imaging system (blur) from the observed degraded image, together with some (statistical) char acteristics of the noise and the original (uncorrupted) image. On the basis of these properties the image restoration process computes an estimate of the original image. Although there are many textbooks addressing the image identification and restoration problem in a general image processing setting, there are hardly any texts which give an indepth treatment of the state-of-the-art in this field. This monograph discusses iterative procedures for identifying and restoring images which have been degraded by a linear spatially invari ant blur and additive white observation noise. As opposed to non-iterative methods, iterative schemes are able to solve the image restoration problem when formulated as a constrained and spatially variant optimization prob In this way restoration results can be obtained which outperform the lem. results of conventional restoration filters."