Human Visual System-based Unequal Error Protection for Robust Video Coding

To increase the overall visual quality of the video services without increasing data rate, a human visual systembased video coding, founded on a hierarchy of the video stream in different levels of importance, is developed. Determining these importance levels takes in count three classification criteria: the position of current image in the group of images (image level), the importance of the motion vectors of macroblocks in the current image (macroblock level) and belonging or not of a pixel in a spatial region of interest (pixel level). At the end of this classification process, an interpolation between the results of the three-level selection allows to establish an index of importance for each macroblock of the image to be encoded. This index determines the type of channel coding to be applied to the corresponding macroblock. Tests have shown that the technique presented in this paper achieves better results in PSNR and SSIM (structural similarity) than an equal error protection technique. Keywords—video coding; unequal error protection; human visual system (HVS); Regions of Interest ROI; Significant Motion Vectors SVM; Classification; index of importance