Optimized and efficient deblurring through constraint conditional modelling

Image deburring technique refers to restoring an image from the degraded version named blurred. Blurring can be caused due to various phenomena such as optical system, motion blur and other phenomena. Moreover, to deblur the image it is essential to know the blurring process characteristics and it i...

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Main Authors: H C, Ravikumar (Author), Karthik, P (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2021-03-01.
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042 |a dc 
100 1 0 |a H C, Ravikumar  |e author 
100 1 0 |e contributor 
700 1 0 |a Karthik, P  |e author 
245 0 0 |a Optimized and efficient deblurring through constraint conditional modelling 
260 |b Institute of Advanced Engineering and Science,   |c 2021-03-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23822 
520 |a Image deburring technique refers to restoring an image from the degraded version named blurred. Blurring can be caused due to various phenomena such as optical system, motion blur and other phenomena. Moreover, to deblur the image it is essential to know the blurring process characteristics and it is one of the difficult task. In past several deblurring algorithm have been proposed to approximate the kernel blur, however they lack the efficiency and expensive to be applied for the real world scenario. In this paper, we have proposed a CCM (constraint conditional model) to deblur the image; it learns the direct mapping from the degraded to the absolute clean image. Moreover, the main aim of CCM is to restore the image in its original form, the best advantage of CCM is that it provides handsome tradeoff between the image quality and efficiency. Moreover CCM is evaluated on the three different standard datasets by considering the different performance metrics and through the comparison analysis observation has made that CCM approach outperforms the other techniques. 
540 |a Copyright (c) 2021 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690 |a Constraint conditional model; Convolution; Deblurring; Image restoring 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 21, No 3: March 2021; 1503-1512 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v21.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23822/14723 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23822/14723  |z Get fulltext