An optimized reconstruction algorithm for point spread Function Based on Slant Step Edge
Journal Title: Remote Sensing - Year 2012, Vol 1, Issue 1
Abstract
The existing slant step edge methods, greatly influenced by the edge? s sub-pixel positioning precision, the Edge spread Function (ESF) Samples5 quality and fitting models of the ES F curve, do not perform-stability and accuracy. An optimized reconstruction algorithm for Point spread Function (PSF) with better precision is proposed using the Slant St EP Edge. The gradient operator is introduced in Edge line fitting to refine the edge points ' sub-pixel positions for greater Accura Cy. The improved method adopts new techniques of moving window in the ESF de-ioising and resampling method to improve ESF Le ' s quality. Finally, robust PSF reconstruction results are obtained by Gaussian function fitting. Experiments demonstrate that the new algorithm shows the very very performance gain in the precision of step edge line fitting and Also the superiority in accuracy and stability of the PSF reconstruction.
Authors and Affiliations
Qu mengya , Zhang yongsheng, Li runsheng
Keywords
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