NDLI: Hybrid higher-order total variation model for multiplicative noise removal

Content Provider	IET Digital Library
Author	Liu, Pengfei
Abstract	As an important, challenging, and difficult problem in image processing, multiplicative noise removal (MNR) has attracted great attention. To this end, many variational methods have been effectively proposed in the past few decades. Among these variational methods, total variation (TV) and its higher-order extensions are very effective, where the former can preserve sharp edges but cause some undesirable staircase effects and the latter can better reduce the staircase effects but sometimes smooth the image details. To overcome the drawbacks while taking full use of their merits, the authors propose a novel hybrid higher-order TV regularisation model for MNR, in which the novelty of the proposed model consists of combining the image prior information of first-order and second-order derivatives to propose a novel higher-order regulariser, named as hybrid higher-order TV (HHTV). More specifically, a more preferable equivalent formulation of HHTV is derived. Then, they use the derived equivalent formulation to design an efficient alternating iterative algorithm to solve the proposed model. Finally, the experimental results demonstrate that the proposed HHTV method outperforms several state-of-the-art methods in terms of image quality and convergence speed.
Starting Page	862
Ending Page	873
Page Count	12
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 5, Apr (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5930
Journal	IET Image Processing
Publisher Date	2019-11-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Convergence Speed Derived Equivalent Formulation HHTV Method Higher-order Extensions Higher-order Total Variation Model Image Denoising Image Details Image Edge Image Prior Information Image Processing Image Quality Image Reconstruction Image Restoration Interpolation And Function Approximation Iterative Method MNR Multiplicative Noise Removal Novel Higher-order Regulariser Novel Hybrid Higher-order TV Regularisation Model Numerical Analysis Optical, Image And Video Signal Processing Preferable Equivalent Formulation Second-order Derivatives Sharp Edge Staircase Effect Undesirable Staircase Effect Variational Method Variational Technique
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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

Single image dehazing and denoising combining dark channel prior and variational models

Variational total curvature model for multiplicative noise removal

A New Total Variation Method for Multiplicative Noise Removal

Edge adaptive directional total variation

Higher order variational multiplicative noise removal model

A new total variation method for multiplicative noise removal (2008)

Stroke width-based directional total variation regularisation for document image super resolution

A New Convex Optimization Model for Multiplicative Noise and Blur Removal

A Variational Model for Staircase Reduction in Image Denoising

Hybrid higher-order total variation model for multiplicative noise removal

Similar Documents

Single image dehazing and denoising combining dark channel prior and variational models

Variational total curvature model for multiplicative noise removal

A New Total Variation Method for Multiplicative Noise Removal

Edge adaptive directional total variation

Higher order variational multiplicative noise removal model

A new total variation method for multiplicative noise removal (2008)

Stroke width-based directional total variation regularisation for document image super resolution

A New Convex Optimization Model for Multiplicative Noise and Blur Removal

A Variational Model for Staircase Reduction in Image Denoising

Hybrid higher-order total variation model for multiplicative noise removal