Dynamic support region-based astronomical image deconvolution algorithm

Physics – Optics

Scientific paper

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Scientific paper

The performance of high-resolution imaging with large optical instruments is severely limited by atmospheric turbulence, and an image deconvolution is required for reaching the diffraction limit. A new astronomical image deconvolution algorithm is proposed, which incorporates dynamic support region and improved cost function to NAS-RIF algorithm. The enhanced NAS-RIF (ENAS-RIF) method takes into account the noise in the image and can dynamically shrink support region (SR) in application. In restoration process, initial SR is set to approximate counter of the true object, and then SR automatically contracts with iteration going. The approximate counter of interested object is detected by means of beamlet transform detecting edge. The ENAS-RIF algorithm is applied to the restorations of in-door Laser point source and long exposure extended object images. The experimental results demonstrate that the ENAS-RIF algorithm works better than classical NAS-RIF algorithm in deconvolution of the degraded image with low SNR and convergence speed is faster.

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