Iterative-Interpolation Super-Resolution Image Reconstruction [electronic resource] : A Computationally Efficient Technique /
Bannore, Vivek.author.
This book presents a novel and hybrid, computationally efficient, reconstruction scheme for solving the problem of super-resolution restoration of high-resolution images from sequences of geometrically warped, aliased and under-sampled low-resolution images. The scheme proposed is referred as the Iterative-Interpolation Super-Resolution (IISR) technique. The optimization-based technique for super-resolution is reinvestigated for comparative analysis to evaluate the accuracy and efficiency of the IISR technique. The significant influence of the regularization term over the fidelity of reconstruction is also analysed. The IISR technique addresses the problem of super-resolution image enhancement in terms of maintaining highest fidelity of reconstruction and a low computational cost to achieve maximum applicability of super-resolution to the real-world applications.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references (p. [109]-113).
to Super-Resolution -- Overview of Super-Resolution Techniques -- Iterative-Interpolation Super-Resolution (IISR) -- Optimization Approach to Super-Resolution Image Reconstruction -- Image Registration for Super-Resolution -- Software Framework -- Conclusion and Future Directions.
This book presents a novel and hybrid, computationally efficient, reconstruction scheme for solving the problem of super-resolution restoration of high-resolution images from sequences of geometrically warped, aliased and under-sampled low-resolution images. The scheme proposed is referred as the Iterative-Interpolation Super-Resolution (IISR) technique. The optimization-based technique for super-resolution is reinvestigated for comparative analysis to evaluate the accuracy and efficiency of the IISR technique. The significant influence of the regularization term over the fidelity of reconstruction is also analysed. The IISR technique addresses the problem of super-resolution image enhancement in terms of maintaining highest fidelity of reconstruction and a low computational cost to achieve maximum applicability of super-resolution to the real-world applications.
Applied mathematics.
Engineering mathematics.
Optical data processing.
Artificial intelligence.
Neuropsychology.
Applications of Mathematics.
Image Processing and Computer Vision.
Artificial Intelligence.
Mathematical and Computational Engineering.
Neuropsychology.

Studies in Computational Intelligence