Retinex based visual identicalness detection for videos corrupted by imaging noise

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.