NDLI: Image enhancement using convolutional neural network to identify similar patterns

Content Provider	IET Digital Library
Author	Lu, Ching Ta Chen, Ruei Han Wang, Ling Ling Lin, Jia An
Abstract	An image may be disturbed by impulse noise during transmission or acquisition. To effectively restore the disturbed image is important for the applications of image processing. This study aims at enhancing the disturbed images by using the convolutional neural network (CNN) to identify similar patterns for the restoration of noisy pixels. In the training phase, each noisy pixel is analysed and compared with the noise-free image to find the closest neighbouring pixels. The pixels in a local window form a micro-pattern. All the captured micro-patterns, whose centre pixel is noisy, become a dataset for the training of a position CNN. The closest neighbouring pixel of a noisy image to the centre one of the noise-free image at the same position of each micro-pattern is selected to be the target. In the enhancement phase, a noisy micro-pattern, where the centre pixel is noisy, is input into the trained position CNN. The top N pixels are recognised and averaged to replace the grey level of the centre pixel. An enhanced pixel is obtained. The experimental results show that the position CNN can well recognise the similar neighbouring pixels and effectively enhance the noisy pixels in an image disturbed by salt-and-pepper noise.
Starting Page	3880
Ending Page	3889
Page Count	10
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 15, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/15
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0560
Journal	IET Image Processing
Publisher Date	2020-12-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Centre Pixel Closest Neighbouring Pixel Computer Vision And Image Processing Technique Convolutional Neural Nets Convolutional Neural Network Disturbed Image Enhanced Pixel Enhancement Phase Image Denoising Image Enhancement Image Processing Impulse Noise N Pixel Noise-free Image Noisy Image Noisy Micropattern Noisy Pixel Optical, Image And Video Signal Processing Similar Neighbouring Pixel Trained Position CNN Training Phase
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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