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Research Article Open Access
The goal of image deblurring is to restore an image within a given area, from a blurred specimen. It is well know that the convolution operator integrates not only the image in the field of view of the given specimen, but also the part of the scenery in the area bordering it. The given results demonstrate the importance of accurate phase recovery, where even a relatively small phase error can have a dramatic effect on the quality of image deconvolution. Under such conditions, the proposed method produces image reconstructions of a superior quality, as compared with the case of Classical Compressed Sensing . Moreover, comparing the results one can see that DS only slightly outperforms Derivative Compressed Sensing in terms of Peak Signal to Noise Ratio and Image estimate obtained with the CCSbased method for phase recovery Structural Similarity Index Measurment .
Deconvolution, derivative compressive sampling , inverse problem, Shack?Hartmann interferometer (SHI)., Aerospace Engineering,Applied Electronics,Applied Sciences,Biomedical Engineering,Botany,Fluid Dynamics.