Image editors typically create a histogram of the image being edited. The histogram plots the number of pixels in the image (vertical axis) with a particular brightness or tonal value (horizontal axis). Algorithms in the digital editor allow the user to visually adjust the brightness value of each pixel and to dynamically display the results as adjustments are made.
Histogram equalization is a popular example of these algorithms. Improvements in picture brightness and contrast can thus be obtained. In the field of
computer vision, image histograms can be useful tools for
thresholding. Because the information contained in the graph is a representation of pixel distribution as a function of tonal variation, image histograms can be analyzed for peaks and/or valleys. This threshold value can then be used for
edge detection,
image segmentation, and
co-occurrence matrices. ==See also==