Image loss concealment using edge-guided interpolation and multi-scale transformation

A novel global edge interpolation, based on new edge-guided interpolation methods for image gap restoration, is presented. The gap restoration is achieved by incorporating the edge-based directional interpolation within a multi-scale DCT/DWT pyramid transform. Two categories of image edges are proposed and utilised in the image gap reconstruction process. First, the local edges, or textures inferred from estimation of the gradients of the neighbouring pixels in various directions, are measured. Second, the global edges, or boundaries between image objects or segments, are estimated by using the Canny edge detector. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, reveal that the proposed method results in improved quality of the image and increase in PSNR by 1 to 5 dB compared to a range of best published works.