Rigid Registration using Sparse Representation Descriptor in MR Images, M.Sc. Thesis Sharif University of Technology ; Manzuri-Shalmani, Mohammad Taghi (Supervisor)
Abstract
In recent years, sparse representation has had a variety of applications in computer vision such as noise reduction, image reconstruction, classification and dimension reduction. In this project, we aim to provide a method of matching the keypoints obtained from the Scale Invariant feature Transform (SIFT) algorithm. In this algorithm is used descriptor instead of intensity . The proposed method, first, extracts the salient points from the images and learns a dictionary-based descriptors corresponding to the points. Then, using the dictionary, it obtains the sparse coefficients for each salient point by which, it determines the correspondence of the salient points in the two images using SVD...
Cataloging briefRigid Registration using Sparse Representation Descriptor in MR Images, M.Sc. Thesis Sharif University of Technology ; Manzuri-Shalmani, Mohammad Taghi (Supervisor)
Abstract
In recent years, sparse representation has had a variety of applications in computer vision such as noise reduction, image reconstruction, classification and dimension reduction. In this project, we aim to provide a method of matching the keypoints obtained from the Scale Invariant feature Transform (SIFT) algorithm. In this algorithm is used descriptor instead of intensity . The proposed method, first, extracts the salient points from the images and learns a dictionary-based descriptors corresponding to the points. Then, using the dictionary, it obtains the sparse coefficients for each salient point by which, it determines the correspondence of the salient points in the two images using SVD...
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