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Multiple Blur Images Restoration -- A Parallel Computing Approach

Authors: Sudha Tiwari; Naazish Rahim; Sandeep Sahu; Nikita Sharma;

Multiple Blur Images Restoration -- A Parallel Computing Approach

Abstract

Image restoration is the process of recovering the original image from the degraded or noisy image. Blind Deconvolution Algorithm can be used where no information about PSF value, it restores image and PSF simultaneously. There are multiple noisy images for deblurring. The first task is original images are degraded by degradation model. It can be done by Gaussian Filter which is low-pass filter. The second task is canny edge detection method is used for identifying the strong and weak edge. The final task is deblured images is recovered by parallel computing task and restored at a time. Once the deblur kernel is estimated using our method. We use this parallel computing approach for the multiple images. A local scheduler done the parallel work. We focus our attention on the problem of restoring multiple images corrupted by blur and noise.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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