Visual reconstruction
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Within-modality registration using intensity-based cost functions
Handbook of medical imaging
Digital Image Warping
Optimally Rotation-Equivariant Directional Derivative Kernels
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
Robust motion estimation under varying illumination
Image and Vision Computing
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
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Affine parameter estimation technique applied to image registration is found useful in obtaining reliable fusion of same object's images taken from different modalities, into single image with strong features. Usually, the minimization in affine parameter estimation technique can be done by least squares in a quadratic way. However, this will be sensitive to the presence of outliers. Therefore, affine parameter estimation technique for image registration calls for methods that are robust enough to withstand the influence of outliers. Progressively, some robust estimation techniques demanding non-quadratic and non-convex potentials adopted from statistical literature have been used for solving these. Addressing the minimization of error function in a factual framework for finding the global optimal solution, the minimization can begin with the convex estimator at the coarser level and gradually introduce non-convexity i.e., from soft to hard redescending non-convex estimators when the iteration reaches finer level of multiresolution pyramid. Comparison has been made to find the performance results of proposed method with the registration results found using different robust estimators.