NDLI: Structure-based interpolation method for restoring the intensity of low-density impulse noise

Content Provider	IET Digital Library
Author	Sanaee, Payam Moallem, Payman Razzazi, Farbod
Abstract	Restoring pixel intensities corrupted by impulse noise has a great impact on the quality of decision-based filters. In this study, the authors’ focus is on intensity restoration of noisy pixels. Their assumption is that noisy pixels are already established by the noise-detection unit being considered as missing data in the image. When the interpolation methods are adopted in the noise-restoration unit of the decision-based filters for the purpose of restoring the intensities of the noisy pixels, two unexpected problems emerge – jagged edges and blurred details. These drawbacks can be ameliorated by using extra information obtained from structures in the images. Their structure-based interpolation method comprises two steps: pre-interpolation and post-interpolation. In the first step (pre-interpolation), the Sibson natural neighbour interpolation is adopted for the initial estimation of the intensities of all noisy pixels. In the second step (post-interpolation, modifying-phase), for each noisy pixel in pre-interpolated image, the intensity variations of the pixels on two adjacent parallel lines, in different directions in their corresponding local windows, are analysed. Based on the obtained structural information, the intensity of the centred noisy pixel is restored more effectively. Since the structures in the images are far more noticeable at low-density impulse noise, the proposed method works more efficiently in this case; however, a gradual improvement is achieved for high-density impulse noise.
Starting Page	1577
Ending Page	1585
Page Count	9
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 9, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0948
Journal	IET Image Processing
Publisher Date	2018-04-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Decision-based Filter Image Filtering Image Restoration Impulse Noise Interpolation Interpolation And Function Approximation Low-density Impulse Noise Noise-detection Unit Numerical Analysis Optical, Image And Video Signal Processing Pixel Intensity Restoration Post-interpolation Method Pre-interpolation Method Sibson Natural Neighbour Interpolation Structure-based Interpolation Method
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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