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The automatic prediction of perceived quality from image data in
general, and the assessment of particular image characteristics or
attributes that may need improvement in particular, becomes an
increasingly important part of intelligent imaging systems. The
purpose of this paper is to propose to the color imaging community in
general to develop a software package available on internet to help
the user to select among all these approaches which is better
appropriated to a given application. The ultimate goal of this project
is to propose, next to implement, an open and unified color imaging
system to set up a favourable context for the evaluation and analysis
of color imaging processes. Many different methods for measuring the performance of a process have been proposed by different researchers. In this paper, we will discuss the advantages and shortcomings of most of main analysis criteria and performance measures currently used. The aim is not to establish a harsh competition between algorithms or processes, but rather to test and compare the efficiency of methodologies firstly to highlight strengths and weaknesses of a given algorithm or methodology on a given image type and secondly to have these results publicly available. This paper is focused on two important unsolved problems. Why it is so difficult to select a color space which gives better results than another one? Why it is so difficult to select an image quality metric which gives better results than another one, with respect to the judgment of the Human Visual System? Several methods used either in color imaging or in image quality will be thus discussed. Proposals for content-based image measures and means of developing a standard test suite for will be then presented. The above reference advocates for an evaluation protocol based on an automated procedure. This is the ultimate goal of our proposal.
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