Moving object completion is a process of completing moving object's missing information based on local structures. Over the past few years, a number of computable algorithms of video completion have been developed, however most of these algorithms are based on the pixel domain. Little theoretical and computational work in video completion is based on the compressed domain. In this paper, a moving object completion method on the compressed domain is proposed. It is composed of three steps: motion field transferring, thin plate spline interpolation and combination. Missing space-time blocks will be completed by placing new motion vectors on them so that the resulting video sequence will have as much global visual coherence with the video portions outside the hole. The experimental results are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

Fast schemes for compressed-domain image size change, are proposed. Fast Winograd DCTs are applied to resizing images by a factor of two to one. First, we speed up the DCT domain downsampling scheme which uses the bilinear interpolation. Then, we speed up other image resizing schemes which use DCT lowpass truncated approximations. The schemes proposed here reduce the computational complexities significantly, while there is no difference in the overall quality of the images compared to previous works.

Visual inpainting is an interpolation problem that restores an image or a frame with missing or damaged parts. Over the past decades, a number of computable models of visual inpainting have been developed, but most of these models are based on the pixel domain. Little theoretical and computational work of visual inpainting is based on the compressed domain. In this paper, a visual inpainting model in the discrete cosine transform (DCT) domain is proposed. DCT coefficients of the non-inpainting blocks are utilized to get block features, and those block features are propagated to the inpainting region iteratively. The experimental results with I frames of MPEG4 are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

Image processing in transform domain has many advantages but it could be suffered from local effects such as a blocking artifact. In this paper, an image processing is performed by weighting coefficients in the compressed domain, i.e., filtering coefficients are appropriately selected according to the processing. Since we find the appropriate factors according to global image enhancement, blocking artifacts are reduced between inter-blocks. Experimental results show that the proposed technique has the advantages of simple computation and easy implementation.