NDLI: Intelligent denoising technique for spatial video denoising for real-time applications

Content Provider	IEEE Xplore Digital Library
Author	Mahmoud, R.O. Faheem, M.T. Sarhan, A.
Copyright Year	2008
Description	Author affiliation: Comput. & Autom. Control Dept., Tanta Univ., Tanta (Faheem, M.T.; Sarhan, A.) \|\| Nile Inst. of Commerce & Comput. Technol., Mansoura (Mahmoud, R.O.)
Abstract	With the wide spread of video usage in many fields of our lives, it becomes very important to develop new techniques for video denoising. Spatial video denoising using wavelet transform has been the focus of the current researches as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered in this work: 2D Discrete Wavelet Transform (2D DWT) and 2D Dual Tree Complex Wavelet Transform (2D DTCWT). Each of these techniques has its advantages and disadvantages. The first technique gives less quality at high levels of noise but consumes less time while the second gives high quality video while consuming long. In this work, we introduce an intelligent denoising system that makes a tradeoff between the quality of the denoised video and the time required for denoising. The system first estimates the noise level in the video frame then accordingly chooses the proper of the two denoising techniques to apply on the frame. The simulation results show that the proposed system is more suitable for real-time applications where the time is critical while giving high quality videos especially at low to moderate levels of noise.
Starting Page	407
Ending Page	412
File Size	529209
Page Count	6
File Format	PDF
ISBN	9781424421152
DOI	10.1109/ICCES.2008.4773037
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-25
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	AWGN Gaussian noise Motion estimation Noise reduction Focusing Additive white noise Video compression Discrete wavelet transforms Optoelectronic and photonic sensors Noise level
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

Temporally-Adaptive MAP Estimation for Video Denoising in the Wavelet Domain

A Real-Time Technique for Spatio–Temporal Video Noise Estimation

Combined Curvelet and Wavelet Denoising

Motion Adaptive Video Denoising in the Wavelet Domain Based on Bivariate Shrinkage

Image Denoising Using Weighted Averaging

Wavelet-based denoising of speech

Influence of the Wavelet Family in the Compression-Denoising Technique on Synthetic and Natural Images

Typhoon Image Denoising in Curvelet Domain

Using wavelets on denoising infrared medical images

Intelligent denoising technique for spatial video denoising for real-time applications

Similar Documents

Temporally-Adaptive MAP Estimation for Video Denoising in the Wavelet Domain

A Real-Time Technique for Spatio–Temporal Video Noise Estimation

Combined Curvelet and Wavelet Denoising

Motion Adaptive Video Denoising in the Wavelet Domain Based on Bivariate Shrinkage

Image Denoising Using Weighted Averaging

Wavelet-based denoising of speech

Influence of the Wavelet Family in the Compression-Denoising Technique on Synthetic and Natural Images

Typhoon Image Denoising in Curvelet Domain

Using wavelets on denoising infrared medical images

Intelligent denoising technique for spatial video denoising for real-time applications