抽象的

Combined method of Blur Deconvolution and HR image reconstruction using Segment Adaptive Gradient Angle Interpolation (SAGA)

Deepa M, Dr.T.V.U.Kirankumar, Muthukumaran S, Mohankumar C

This paper presents, for the first time, a combined blur deconvolution and edge-directed interpolator based on adaptive gradient angle interpolation locally defined, straight line approximations of image isophotes for super resolution. The proposed blur estimation process is supported by an edge-emphasizing smoothing operation, which improves the quality of blur estimates by enhancing strong soft edges toward step edges, while filtering out weak structures. For better performance, the blur estimation is done in the filter domain rather than the pixel domain using the gradients of the Low Resolution and High Resolution images. The proposed method can accommodate arbitrary scaling factors, provides state-of-the-art results in terms of PSNR as well as other quantitative visual quality metrics, and has the advantage of reduced computational complexity that is directly proportional to the number of pixels..