Digital images are enhanced for extracting the additional information that is not by itself perceivable prior to enhancement. Histogram modeling is considered one of the well known methods for enhancing the images. Histogram being a global description of an image in terms of probabilities of various intensity levels Histogram modeling is normally achieved in two steps namely histogram equalization and histogram specification. Histogram equalization and histogram specification have been widely used to enhance information in a gray scale image, with histogram specification having the advantages of allowing the output histogram to be specified as compared to the histogram equalization which attempts to produce an output histogram that is uniform. Unfortunately, expanding histogram techniques to colour images is not straightforward. Since humans are sensitive to chromatic changes, care must be taken to ensure that incorrect colours are not produced. Additionally, expanding the 1-D histogram used in gray level histogram techniques to a joint histogram (usually of three variables representing the primary colours of red, green and blue) can yield specified histograms which have no physical meaning hence making it difficult to determine the set of histograms required for the desired enhancement. Method of gray level histogram specification is extended to colour images by performing histogram specification on intensity, saturation and hue components. These methods take into account the relationship between the intensity and saturation components while yield specified histograms that produce natural looking results.

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Image Enhancement Intensity Saturation Histogram Histogram Equalization Histogram Specification