7 September 2010 Analysis of the selection of overlapping region of sectioned restoration for images with space-variant point spread function
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Abstract
Classical image restoration is mostly base on the image deconvolution under the assumptions of linear system transformation, stationary signal statistics and stationary, signal independent noise. Unfortunately, the assumptions are not always accurate in real problems. For example, the optical aberrations, local defocus, local motion blur, temperature variation, flexible medium, and non-stationary platform all cause the uncertain different degradation in different area of the images. Therefore, overlapping-region sectioned restoration is suggested to reconstruct such blurred images with space-variant point spread function (SVPSF). First of all, the full image is divided into several sub-sections, in which the PSF nominally space invariant (SI). After the restoration with SI algorithm, the sub-frames are spliced to construct the composite full-frame. Moreover, overlapping extension is employed to isolate edge-ringing effects from circular convolution between the different restored sub-frames. In this paper, with the help of SSIM (Structural Similarity) and GRM (Gradient Ringing Matrix) image quality assessment approaches, we discussed the selection of overlapping region of the sectioned restoration with different algorithms, for images with signal to noise ratio (SNR) from 25db to 40db. Our investigation proves that the restored image quality is best when the overlapping region as wide as the energydistribution- area of degradation function.
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Xiaoping Tao, Xiaoping Tao, Jufeng Zhao, Jufeng Zhao, Huajun Feng, Huajun Feng, Qi Li, Qi Li, Zhihai Xu, Zhihai Xu, Yueting Chen, Yueting Chen, } "Analysis of the selection of overlapping region of sectioned restoration for images with space-variant point spread function", Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 77982C (7 September 2010); doi: 10.1117/12.860014; https://doi.org/10.1117/12.860014
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