DEFOCUSED IMAGE RESTORATION CONFIDENCE INCREASING BY IMPROVING ROUNDING ERRORS CORRECTIONS
DOI:
https://doi.org/10.15588/1607-3274-2016-3-8Keywords:
image reconstruction, defocusing, Fourier transform, distortion operator, deconvolution.Abstract
This paper presents a method of improving the quality of the restoration of defocused images by reducing the effect of rounding errors when sampling on the reconstructed image. The rounding error can be effectively controlled by knowing the nature of the restored image and its distortions. Algorithm that restore lost during rounding values of pixels need to be built based on knowledge of the nature of the image, the required accuracy and the permissible speed of the algorithm. The work contains an example of linear interpolation usage at the source image preprocessing stage as the basis for the construction of refined pixel values of the reconstructed image from the discrete values of the pixels of the original defocused image. The proposed method is not tied to a specific deconvolution algorithm and its use in a pair with any of them gives better results. The paper considers the joint use of presented method with the inverse filter.This paper presents a practical example of image reconstruction based on a linear interpolation of the pixels of the original image. It is
shown that the proposed method affects a reduction of error recovery from about 3% to 20%, depending on the size and specific images. It
showed a decrease in the error recovery with increasing the size of the original image defocused.
References
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Copyright (c) 2016 A. E. Kovnir, K. E. Stepanenko, M. B. Ilyashenko
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