Constellation, le dépôt institutionnel de l'Université du Québec à Chicoutimi

Résumé

Image based rendering (IBR) has been the most Important and rapid developed techniques in the computer graphics and virtual reality fields these years. Image mosaic which is one of the hot topics of IBR is also becoming research interests of many researchers in the image processing and computer vision fields. Its application covers the areas of virtual scene construction, remote sensing, medical image and military affairs etc. However, some difficult issues need to be studied further, including new optimization methods for image registration, new accelerating methods for image stitching etc, which are the main topics of this thesis.

First, as the precision and automatic degree of image mosaic suffers from the algorithm of image registration, a new image stitching optimization method based on maximum mutual information is presented in this thesis. The main idea of the new method is to combine PSO algorithm with wavelet multiresolution strategy and parameters of PSO are adapted along with the resolution of the images.The experiments show that this method can avoid registration process to get stuck into local extremes in image interpolation operations and finds the optimal exchange through limited iterations computation, and obtain subpixel registration accuracy in process of image stitching.

Secondly, to solve the problem of image blur stitching when the geometric deformation and the changes of the scale factor among images are serious, a new method based robust features matching is proposed in this thesis. Firest, it searches overlap area between two images by using phase correlation, and then detects Harris comer points in the overlap areas which are reduced to different scale images by adopting multi resolution pyramid construction. This method can solve the Harris arithmetic operator robust characteristics inspection algorithm for the scale effects. In order to improve the running performance of image feature matching, a dimension reduction method of high dimension feature vector is proposed based on PCA. And last the globe parameters are optimized by Lmeds to realize images mosaic. The experiments prove that the methods proposed by this thesis can reduce the computation cost with guarantee of image mosaic quality.