NDLI: Image denoising using fractional integral

Content Provider	IEEE Xplore Digital Library
Author	Huang Guo Xu Li Chen Qing-li Wang Ming-rong
Copyright Year	2012
Description	Author affiliation: School of Physics and Electronics, Leshan Normal University Leshan China (Xu Li; Chen Qing-li; Wang Ming-rong) \|\| Laboratory of Intelligent Information Processing and Application, Leshan Normal University, Leshan China (Huang Guo)
Abstract	In order to preserve more image details information while image denoising, the fractional integral operator was introduced to signal processing. The method proposed in this work constructed the corresponding mask of image denoising by setting a smaller fractional order, and controlled the effect of image denoising by the way of iteration, so it achieved fine-tuning of image denoising. The experimental results show that the image denoising algorithm based on fractional integral proposed in this work compared with the traditional image denoising algorithm not only enhances the signal-to-noise ratio of image but also better retains the edge and texture details of image.
Starting Page	107
Ending Page	112
File Size	960373
Page Count	6
File Format	PDF
ISBN	9781467300889
e-ISBN	9781467300896
DOI	10.1109/CSAE.2012.6272738
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wiener filters Signal noise ratio Image edge detection Fractional integral Filtering algorithms Iteration Image denoising Signal to noise ratio
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Denoising 3D biomedical images with fractional-order integral calculus

Denoising Images using Wiener Filter in Directionalet Domain

Adaptive filters based on local estimates

Image Denoising via Clustering-Based Sparse Representation over Wiener and Gaussian Filters

A Geometric Mean Based Adaptive Local Noise Removal Algorithm

Noise filtering in ultrasound images using Gravitational Search Algorithm

A novel algorithm of image denoising and edge preserving based on discrete grey model

Hybrid Edge Detector

Adaptive schemes for noise filtering and edge detection by use of local statistics

Image denoising using fractional integral

Similar Documents

Denoising 3D biomedical images with fractional-order integral calculus

Denoising Images using Wiener Filter in Directionalet Domain

Adaptive filters based on local estimates

Image Denoising via Clustering-Based Sparse Representation over Wiener and Gaussian Filters

A Geometric Mean Based Adaptive Local Noise Removal Algorithm

Noise filtering in ultrasound images using Gravitational Search Algorithm

A novel algorithm of image denoising and edge preserving based on discrete grey model

Hybrid Edge Detector

Adaptive schemes for noise filtering and edge detection by use of local statistics

Image denoising using fractional integral