Edge Halo Reduction for Projections onto Convex Sets Super Resolution Image Reconstruction

In this paper, we propose three improvements in the quality of high-resolution image for super-resolution reconstruction method based on projections onto convex sets (POCS). In order to improve the blur edge caused by bilinear interpolation, the wavelet bi-cubic interpolation is proposed to obtain the initial image estimation for reconstruction algorithm based on POCS. The point spread function (PSF) with edge-preserving property is proposed to reduce the amount of edge Halo in reconstruction result. The length-variable relaxation projection parameter, obtained by the correlation between low-resolution observation frames and reference frame, is adopted to reduce motion estimate error. Experiment results show that the proposed algorithm effectively reduces the amount of edge halo and obviously improves the quality of reconstructed high-resolution image.