A moment-based method is proposed to estimate the illumination change between two images containing affinetransformed objects. The change is linearly modeled with parameters to be estimated by histograms due to its invariance of translation, rotation, and scaling. The parameters can be correctly estimated for an appropriate illumination change by normalizing the moments of the histograms.

This paper presents a novel and practical face-assisted video coding scheme to enhance the visual quality of the face region in videophone applications. A low-complexity skin-color-based face detection and tracking scheme is proposed to locate the human face regions in realtime. After classifying the macroblocks (MBs) into the face and non-face regions, we present a dynamic distortion-weighting adjustment (DDWA) scheme to skip encoding the static non-face MBs, and the saved bits are used to compensate the face region by increasing the distortion weighting of the face MBs. The quality of the face regions will thus be largely enhanced. Moreover, the computation originally required for encoding the skipped MBs can also be saved. The experimental results show that the proposed method can significantly improve the PSNR and the subjective quality of face regions, while the degradation introduced on the non-face areas is relatively invisible to human perception. The proposed algorithm is fully compatible with the H. 263 standard, and the low complexity feature makes it well suited to be implemented for real-time applications.