| With the quick development of information technique and computer science, the techniques about image processing, automatic target recognition and computer vision have been widely applied in many fields, such as industries, national defence, aeronautics and aerospace. In this thesis, the following three problems are discussed in detail:1. The image enhancement problem for degraded images with less gray levels and low contrasts. Image enhancement is an important part of image preprocessing, and enhanced images suitable for different applications can be obtained using different image enhancement methods. The traditional image enhancement approaches include gray-scale transformation, histogram modification, histogram equalization, image smoothing and Wiener filtration. The theory of fuzzy sets has been used to deal with image enhancement problems for degraded images in which the image edges are uncertain and inaccurate. For those kinds of images, to some extent, the good enhancement effect can be obtained using the fuzzy sets-based image enhancement method instead of the traditional image enhancement approaches. The gray level maximum has not been changed in the classical fuzzy enhancement method proposed by S. K. Pal, so this kind of image enhancement method is not fit for the enhancement problem of degraded images with less gray levels and low contrasts; the fact that the value domain of membership function of gray levels is not normalization form, i.e. [0,1], is another disadvantage of the traditional fuzzy enhancement means. To deal with the problems mentioned above, a generalized iterative fuzzy enhancement algorithm is proposed in this thesis that consists of a three-stage procedure, i.e., image filtering, fuzzy enhancement and gray-level transformation. The generalized fuzzy enhancement method extend the gray level range of the original image, and a canonical form of membership function in the stage of fuzzy enhancement is presented which remains the advantages of the original fuzzy enhancement and the gray level transformation while transforming the membership function of the gray scale to [0,1]. A new image quality assessment criterion is suggested on the basis of the statistical features of the gray-level histogram of images to control the iterative procedure of the proposed image enhancement algorithm. Computer simulation results showedthat this new enhancement method is more suitable than fuzzy enhancement and gray-level transformation for handling the enhancement problems of images with less gray levels and low contrasts.2. The design problem of edges detector steering orientation. Since edges in images possess very important information about objects in image processing and analyzing, how to extract edges effectively and rapidly becomes an imperative issue. The results of image analyzing and object recognition have a close relationship with the performance of edges detector. Generally, edges in some specified directions can be only detected by most of edges detectors, and detecting edges in many different orientations using usual convolution means is very costly computationally. To handle this problem, a novel adaptive filter for orientation parameter design technique is proposed in this thesis according the theory of One-parameter Transformation Group. An algorithm for the convolution of this filter and an image is also given. The filter, after this parameter changes, can be represented in form of the linear combination of a fixed, finite set of basis filters. When this kind of filters are convoluted with an image in different orientations, the computing efficiency is improved remarkably. A simulation example for edge-detection is given to demonstrate validity of the adaptive filter.3. The design and application problem of the vision system for a six-joint robot manipulator. The automatic recognition of a workpiece and determining its position and orientation (pose) is a prerequisite for implementing production modernization, and thereby can improve productive effici...
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