Improved Edge Refinement Filter with Entropy Feedback Measurement for Retrieving Region of Interest and Blind Image Deconvolution
This study proposes an improved edge refinement filter with entropy feedback measurement for locating an optimal region of interest (ROI) in blurry images. This technique is inspired by He et al.'s algorithm and enhanced by introducing a suitable filter to obtain smooth unwanted pixels whilst...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Stefan cel Mare University of Suceava
2020-02-01
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Series: | Advances in Electrical and Computer Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.4316/AECE.2020.01010 |
Summary: | This study proposes an improved edge refinement filter with entropy feedback measurement for locating
an optimal region of interest (ROI) in blurry images. This technique is inspired by He et al.'s algorithm
and enhanced by introducing a suitable filter to obtain smooth unwanted pixels whilst retaining important
and significant edges. This approach led to an accurate retrieval of ROI and a considerably precise image
restoration within a blind deconvolution framework. Results show that the proposed method is more competitive
than existing techniques and achieves better performance in terms of peak signal-to-noise ratio, kernel
similarity index and error ratio. |
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ISSN: | 1582-7445 1844-7600 |