Abstract: In order to obtain high quality image information under the condition of compact optical lens structure, an approach for image restoration and reconstruction based on simple lenses computational imaging was proposed. First, by analyzing the characteristics of the Space Variant Point Spread Function (SVPSF) of the optical system, the method of SVPSF acquisition and measurement was presented. Then, the image sectioned restoration algorithm with SVPSF based adaptive sparse prior information was developed, which was used successfully in the restoration of blurry images through simple lenses. To validate the algorithm, the imaging results were obtained from through simple lenses imaging by the digital simulation and real images. Experimental results indicate that the algorithm can efficiently suppress the ringing effect and preserve the details of the images.

Key words: computer application, information processing technology, computational imaging, space-variant point spread function (SVPSF), sectioned restoration method