A post-processing algorithm for performance enhancement of remote video-based monitoring systems

This work presents a real-time post-processing algorithm developed for enhancing the performances of remote JPEG-based video surveillance applications, seriously degraded by transmission over noisy channels. The aim of the algorithm is to distinguish between blocks changes due to variations in the observed scene and noise-altered blocks, which contain errors due to channel noise and can be corrected exploiting the strong spatio-temporal redundancy of the encoded digital source without any side information. Experimental results, obtained through JPEG transmission simulations performed in the context of a remote video-surveillance system devoted to detection of abandoned objects, show a good improvement both in terms of perceptive quality and of the performance of the overall video-surveillance system