Journal Paper

Paper Title - A Review: Multi-Frame Sparse Super-Resolution with Blind De-convolution


Abstract
Super-Resolution (SR) is a process of estimating High-Resolution (HR) image from Low-Resolution (LR) image in order to increase spatial and/or temporal resolution.SR algorithms uses a linear observation model to derive the relation between the recorded LR and Full-Resolution (FR) images. For this purpose, a multi-frames SR for deep comparison of the FR image, Interpolated view and Zero-filled view from the LR image is used. For the recovery of ill-posed SR problem, Regularization with structure modulated sparse representation method is used. Finally, the Blur estimation process is carried out on the edges to estimate both true image and the blur from the degraded image using blind de-convolution algorithm. Keywords - Blind de-convolution, Interpolation-based Super Resolution, Zero filled view, sparse representation method and structure modulation


Author - Aniket Garade, Prajakta Deshpande, Swapnali Kore, S.K.Shah, R. P. Patil

Citation - Aniket Garade   ,   Prajakta Deshpande   ,   Swapnali Kore   ,   S.K.Shah   ,   R. P. Patil   ,   Aniket Garade, Prajakta Deshpande, Swapnali Kore, S.K.Shah, R. P. Patil " A Review: Multi-Frame Sparse Super-Resolution with Blind De-convolution " , International Journal of Industrial Electronics and Electrical Engineering , Volume-5,Issue-4  ( Apr, 2017 )

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| Published on 2017-06-20