By Topic

A fast and reliable algorithm for video noise estimation based on spatio-temporal sobel gradients

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Shih-Ming Yang ; Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan ; Shen-Chuan Tai

A fast and reliable spatio-temporal algorithm for estimating additive white Gaussian noise (AWGN) in video sequences is proposed. The input video is divided into right cuboids. Estimations are made on three independent domains (spatial, temporal-horizontal, and temporal-vertical). Inside each domain, homogeneous blocks are first identified based on Sobel gradients with an adaptive and self-determined threshold. The selected blocks are then filtered by a Laplacian operator. The average of the filtering convolutions provides the estimated noise variance for each domain. The arithmetic average of these three estimated variances is computed to be the final estimated noise variance. Experimental results show that the proposed algorithm achieves better performance and maintains low complexity for a variety of video sequences over a large range of noise variances.

Published in:

Electrical, Control and Computer Engineering (INECCE), 2011 International Conference on

Date of Conference:

21-22 June 2011