DCT quantization noise in compressed images

In lossy image compression schemes utilizing the discrete cosine transform (DCT), quantization of the DCT coefficients introduces error in the image representation and a loss of signal information. At high compression ratios, this introduced error produces visually undesirable compression artifacts that can dramatically lower the perceived quality of a particular image. This paper provides a spatial domain model of the quantization error based on a statistical noise model of the error introduced when quantizing the DCT coefficients. The resulting theoretically derived spatial domain quantization noise model shows that in general the compression noise in the spatial domain is both correlated and spatially varying. This provides some justification to many of the ad hoc artifact removal filters that have been proposed. More importantly, the proposed noise model can be incorporated in a post-processing algorithm that correctly incorporates the spatial correction of the quantizer error. Experimental results demonstrate the effectiveness of this approach.