Abstract:
Decolorization also well-known as color2gray image conversion is useful for monotone display
and printing of images. Meaningful structure may vanish when a color image is transformed
to a gray-scale image. Despite of its wide real world applications, adequate efforts
has been made on image quality metric that can be correlated with perceived quality of images.
Subjective quality evaluation is time consuming and is susceptible to personal bias thus
objective quality perception model has been suggested in this research paper. This research
proposes an algorithm consisting of three quality metrics, i.e. local complexity measure,
contrast and edge density. The three metrics are integrated to yield an image quality assessment
results. The experiments performed on benchmark images shows that the proposed
algorithm evaluates images on the basis of content preservation and true contrast loss. The
method is unique in its ability to measure image quality based on local, glocal and global
level separately and mirrors multi-resolution analysis of visual data. It is first attempt among
many to develop objective quality measurement model with these metrics that quantitatively
evaluates gray scale image results.
