Improve the Quality of the Edge and the Motion Estimation of Super-resolution Image Reconstruction

The projection onto convex sets algorithm is widely used for super-resolution image reconstruction. To address the fuzzy edge problems arising from conventional POCS super-resolution image reconstruction algorithm , four edge directions of 0 °, 45 °, 90 °, 135 °were detected first respectively with the second order gradient. When forming a reference frame, if an edge existed，adaptive weighted factor was obtained by calculating its one-step gradient，and then the weighted interpolation was implemented．Otherwise，linear interpolation was adopted. In motion estimation, the SURF matching algorithm was used to improve the robustness and real-time.At the same time, the SURF algorithm was utilized to match the rotational images to enhance the matching flexibility.When revising a reference frame, the point spread function was defined respectively if its center was on the four edges. The proposed POCS algorithm was tested both in the simulated and real data, which were evaluated with full reference image quality assessment and no reference image quality assessment respectively, and the results show that our method can significantly improve the quality of the reconstructed image compared with the traditional POCS algorithm.