Support Vector Machine (SVM) based compression artifact-reduction technique

A compression artifact-reduction algorithm based on support vector regression is proposed. The algorithm belongs to a broad family of standard reconstruction methods, but a standardization model is determined from a set of training samples of original images and the corresponding noise-corrupted version. As opposed to artifact-reduction methods specific to each type of compression artifact ( e.g., blocking, ringing, etc.), we treat such artifacts as a manifestation of the same problem, which is the quantization of DCT coefficients. In the testing step, the algorithm tries to undo the effect of quantization by using the relationship between the original and artifact-corrupted image, determined during the training step. Experimental results exhibit significant reduction in all types of compression artifacts..