Design and Verification of Super-Resolution Reconstruction Algorithm for Remote Sensing Image Based on PSF Estimation
摘要
To improve the spatial resolution of remote sensing images, an improved Projections onto Convex Sets (POCS) super-resolution algorithm based on Point Spread Function (PSF) estimation is proposed. Obtaining PSF from system design or remote sensing image, we use it as a projection operator to simulate the real degradation process of the satellite imaging system, and improve the reconstruction accuracy. To evaluate its performance, we compared it with the classic POCS algorithm, the PSNR/SSIM of the super-resolution image reconstructed by our algorithm is improved from 24.32dB/0.77 to 25.73dB/0.82, and the visual effect of the image is significantly enhanced.