Histogram Equalization of Color Images
The above describes histogram equalization on a grayscale image. However it can also be used on color images by applying the same method separately to the Red, Green and Blue components of the RGB color values of the image. However, applying the same method on the Red, Green, and Blue components of an RGB image may yield dramatic changes in the image's color balance since the relative distributions of the color channels change as a result of applying the algorithm. However, if the image is first converted to another color space, Lab color space, or HSL/HSV color space in particular, then the algorithm can be applied to the luminance or value channel without resulting in changes to the hue and saturation of the image. There are several histogram equalization methods in 3D space. Trahanias and Venetsanopoulos applied histogram equalization in 3D color space However, it results in “whitening” where the probability of bright pixels are higher than that of dark ones. Han et al. proposed to use a new cdf defined by the iso-luminance plane, which results in uniform gray distribution.
Read more about this topic: Histogram Equalization
Famous quotes containing the words color and/or images:
“In Florida consider the flamingo,
Its color passion but its neck a question.”
—Robert Penn Warren (1905–1989)
“It is not the literal past that rules us, save, possibly, in a biological sense. It is images of the past.... Each new historical era mirrors itself in the picture and active mythology of its past or of a past borrowed from other cultures. It tests its sense of identity, of regress or new achievement against that past.”
—George Steiner (b. 1929)