Introduction - If you have any usage issues, please Google them yourself
Many applications of histograms for the purposes
of image processing are well known. However, applying this
process to the transform domain by way of a transform coefficient
histogram has not yet been fully explored. This paper proposes
three methods of image enhancement: a) logarithmic transform
histogram matching, b) logarithmic transform histogram shifting,
and c) logarithmic transform histogram shaping using Gaussian
distributions. They are based on the properties of the logarithmic
transform domain histogram and histogram equalization. The
presented algorithms use the fact that the relationship between
stimulus and perception is logarithmic and afford a marriage
between enhancement qualities and computational efficiency. A
human visual system-based quantitative measurement of image
contrast improvement is also defined. This helps choose the best
parameters and transform for each enhancement. A number of
experimental results are presented to illustrate the performanc