Histogram Equalization Algorithm for Variable Gray Level Mapping

The traditional histogram equalization algorithm is likely to cause information loss. The paper introduced a gray level mapping algorithm in which information entropy remains the same. The algorithm adjusting the gray scale transformation of the image, introduces a new transformation formula parameter beta, and makes the spacing of two adjacent gray levels extend in the new mapped histogram. So that it avoids excessive gray pixel merger and excessive bright image. The selection rule of parameter beta for different gray levels images is given. Experiments show that the improved algorithm may effectively improve visual effects under the premise of the same information entropy.