Institute for Data Analysis and Visualization

Traditional quality measures for image coding, such as the peak signal to noise ratio, assume that the preservation of the original image is the desired goal. However, pre-processing images prior to encoding, designed to remove noise or unimportant detail, can improve the overall performance of an image coder. Objective image quality metrics obtained from the difference between the original and coded images cannot properly assess this improved performance. This paper proposes a new methodology for quality metrics that differentially weighs the changes in the image due to pre-processing and encoding. These new quality measures establish the value of pre-processing for image coding and quantitatively determine the performance improvement that can be thus achieved by JPEG and wavelet coders.