Image registration and super-resolution mosaicing Ye, Getian en_US 2022-03-22T09:03:24Z 2022-03-22T09:03:24Z 2005 en_US
dc.description.abstract This thesis presents new approaches to image registration and super-resolution mosaicing as well as their applications. Firstly, a feature-based image registration method is proposed for a multisensor surveillance system that consists of an optical camera and an infrared camera. By integrating a non-rigid object tracking technique into this method, a novel approach to simultaneous object tracking and multisensor image registration is proposed. Based on the registration and fusion of multisensor information, automatic face detection is greatly improved. Secondly, some extensions of a gradient-based image registration method, called inverse compositional algorithm, are proposed. These extensions include cumulative multi-image registration and the incorporation of illumination change and lens distortion correction. They are incorporated into the framework of the original algorithm in a consistent manner and efficiency can still be achieved for multi-image registration with illumination and lens distortion correction. Thirdly, new super-resolution mosaicing algorithms are proposed for multiple uncompressed and compressed images. Considering the process of image formation, observation models are introduced to describe the relationship between the superresolution mosaic image and the uncompressed and compressed low-resolution images. To improve the performance of super-resolution mosaicing, a wavelet-based image interpolation technique and an approach to adaptive determination of the regularization parameter are presented. For compressed images, a spatial-domain algorithm and a transform-domain algorithm are proposed. All the proposed superresolution mosaicing algorithms are robust against outliers. They can produce superresolution mosaics and reconstructed super-resolution images with improved subjective quality. Finally, new techniques for super-resolution sprite generation and super-resolution sprite coding are proposed. Considering both short-term and long-term motion influences, an object-based image registration method is proposed for handling long image sequences. In order to remove the influence of outliers, a robust technique for super-resolution sprite generation is presented. This technique produces sprite images and reconstructed super-resolution images with high visual quality. Moreover, it provides better reconstructed low-resolution images compared with low-resolution sprite generation techniques. Due to the advantages of the super-resolution sprite, a super-resolution sprite coding technique is also proposed. It achieves high coding efficiency especially at a low bit-rate and produces both decoded low-resolution and super-resolution images with improved subjective quality. Throughout this work, the performance of all the proposed algorithms is evaluated using both synthetic and real image sequences. en_US
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri en_US
dc.subject.other Automatic face detection en_US
dc.subject.other image compression en_US
dc.subject.other image fusion en_US
dc.subject.other image registration en_US
dc.subject.other information fusion en_US
dc.subject.other mosaicing en_US
dc.subject.other multisensor image en_US
dc.subject.other multi-sprite techniques en_US
dc.subject.other object tracking en_US
dc.subject.other super-resolution en_US
dc.subject.other surveillance en_US
dc.subject.other video coding en_US
dc.title Image registration and super-resolution mosaicing en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Ye, Getian
dspace.entity.type Publication en_US
unsw.relation.faculty UNSW Canberra
unsw.relation.originalPublicationAffiliation Ye, Getian, Information Technology & Electrical Engineering, Australian Defence Force Academy, UNSW en_US School of Engineering and Information Technology *
unsw.thesis.degreetype PhD Doctorate en_US
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