Retinex based visual identicalness detection for videos corrupted by imaging noise

Xin Jin*, Satoshi Goto, Qionghai Dai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Detecting the visually identical regions among successive frames for noisy videos, called visual identicalness detection (VID) in this paper, is a fundamental tool in video applications for lower power consumption and higher efficiency. In this paper, instead of performing VID on the original video signal or on the de-noised video signal, a Retinex based VID approach is proposed to perform VID on the Retinex signal to eliminate the noise influence introduced by imaging system. Several Retinex output generation approaches are compared, within which the proposed Cohen-Daubechies-Feauveau wavelet based approach is demonstrated to have better efficiency in detection and higher adaptability to the video content and noise severity. Compared with approaches performing detection in the de-noised images, the proposed algorithm presents up to 4.78 times higher detection rate for the videos with moving objects and up to 30.79 times higher detection rate for the videos with static scenes, respectively, at the same error rate. Also, an application of this technique is provided by integrating it into an H.264/AVC video encoder. Compared with compressing the de-noised videos using the existing fast algorithm, an average of 1.7 dB performance improvement is achieved with up to 5.47 times higher encoding speed. Relative to the reference encoder, up to 32.47 times higher encoding speed is achieved without sacrificing the subjective quality.

Original languageEnglish
Pages (from-to)1187-1201
Number of pages15
JournalSignal Processing: Image Communication
Issue number9
Publication statusPublished - 2013 Oct


  • Identicalness detection
  • Noise robust technique
  • Retinex theory
  • Video applications

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Software
  • Electrical and Electronic Engineering


Dive into the research topics of 'Retinex based visual identicalness detection for videos corrupted by imaging noise'. Together they form a unique fingerprint.

Cite this