Remote sensing image restoration: adaptive reciprocal cell recovery technique
This study aims to study the reason of acquisition and degradation of remote sensing image system and select the most appropriate de-blurring method in the process of repairing the adaptive reciprocal cell. was used to find out the adaptive reciprocal cell in the image system and regularization method was used to perform image restoration. This paper applied non-local model, TV model and ARCTV model to perform de-blurring and the Matlab software experimental platform for result analysis and comparison. It was found that the SNR value of the ARCNLM model was higher than that of the other models and the MSE value of the ARCNLM model was lower than that of the other models, suggesting that the de-blurring effect of the ARCNLM model was better, leaving images with clear edges and no folding phenomenon. The improved ARCNLM model had better de-blurring effects and could be promoted for wide application.
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