Abstract
In this chapter, a modified, regularized image restoration algorithm useful in reducing blocking artifacts in predictive-coded (P) pictures of compressed video, based on the corresponding image degradation model, is presented. Since most video coding standards adopt a hybrid structure of macroblock-based motion compensation (MC) and block discrete cosine transform (BDCT), the blocking artifacts occur at both the block boundary and block interior, and the degradation process due to quantization is generated on just differential images. Based on observation, a new degradation model is needed for differential images and the corresponding restoration algorithm, which directly processes the differential images before reconstructing decoded images. For further removal of both kinds of blocking artifacts, the restored differential image must satisfy two constraints: directional discontinuities on the block boundary and on the block interior. These constraints have been used for defining convex sets for restoring differential images. In-depth analysis of differential domain processing is presented in the appendix and serves as the theoretical basis for justifying differential domain image processing. Experimental results also show significant improvement over conventional methods in the sense of both objective and subjective criteria.
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Abidi, M.A., Gribok, A.V., Paik, J. (2016). Enhancement of Compressed Video. In: Optimization Techniques in Computer Vision. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-46364-3_9
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DOI: https://doi.org/10.1007/978-3-319-46364-3_9
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