Quality measurement and use of pre-processing in image compression

Abstract

Traditional quality measures for image coding, such as the p e a ksignal 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 di erence b e t ween the original and coded images cannot properly assess this improved performance. This paper proposes a new methodology for quality metrics that di erentially 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 b ethus achieved by JPEG and wavelet coders.

Reinforced Contrast Adaptation

“…Low quality digital images can seriously affect the way an image is interpreted, introducing errors in analysis or eliminating the image's usefulness in a industrial or medical environment. [1][2][3][4]6,8,9,11,13,17 The fundamental problem of image enhancement is that every person judges the quality of an image differently. When manipulating and enhancing images, there is not one ideal outcome that will satisfy everyone as every person has a different subjective perception.…”