SIFT-based image registration procedure is the SIFT feature matching algorithm for matching feature points at home and abroad a hot area of research and the difficulties in matching their ability to deal with translation between two images, rotation, affine transformation to match the case of problems, and even to some extent in any angle images will also be able to match the characteristics of a more stable capacity

SIFT-matlab
...........\affine.m
...........\build_pyramid.m
...........\construct_key.m
...........\detect_features.asv
...........\detect_features.m
...........\drawbox.m
...........\eliminate_edges.m
...........\example



...........\.......\script_example.m
...........\filter_gaussian.m
...........\filter_laplacian.m
...........\find_extrema.m
...........\find_features.m
...........\fit_parabola.m
...........\fit_paraboloid.m
...........\fmransac_test2.m
...........\f_class.m
...........\gauss1d.m
...........\gauss2dx.m
...........\getpts.m
...........\get_dvtime.m



...........\interp.m
...........\kill_edges.m
...........\make_cost.m
...........\match_dv_odometry.m
...........\motion_corr.m
...........\motion_corr2.m
...........\mv2.m
...........\plotpoints.m
...........\plot_matched.m
...........\process_loop.m
...........\refine_features.m
...........\resample_bilinear.asv
...........\resample_bilinear.m
...........\script_example.m
...........\showfeatures.m
...........\show_plist.m
...........\show_points.m
...........\structure2.m
...........\symmetric_match.m
...........\test.m
...........\test2.m
...........\test_jy.m
...........\Untitled4.asv

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