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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationInECCE 2011 - International Conference on Electrical, Control and Computer Engineering
Pages191-195
Number of pages5
DOIs
Publication statusPublished - 2011 Aug 18
Event1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011 - Kuantan, Malaysia
Duration: 2011 Jun 212011 Jun 22

Publication series

NameInECCE 2011 - International Conference on Electrical, Control and Computer Engineering

Other

Other1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011
CountryMalaysia
CityKuantan
Period11-06-2111-06-22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A fast and reliable algorithm for video noise estimation based on spatio-temporal Sobel gradients'. Together they form a unique fingerprint.

Cite this