Image Contrast Enhancement by Constrained Local Histogram Equalization

Object-Based Image Enhancement Technique for Gray Scale Images

“…In terms of dilation and erosion another pair of morphological operations are defined known as closing and opening given by (4) and (5) respectively.. …”

“…Image enhancement techniques are widely used in many real time applications. The contrast enhancement in digital images can be handled by using various point processing techniques [2]- [7] like power law, logarithmic transformations and histogram equalization(HE).Image enhancement using power law transformations depends upon the gamma values, if the gamma value exceeds 1, the contrast is reduced.The logarithmic transformation [2]- [4] improve the contrast of the image, but increases the overall brightness.The most widely used technique of Contrast enhancement is Histogram Equalization (HE) [1]- [5], which works by flattening the histogram and stretching the dynamic range of the gray-levels using the cumulative density function of the image. However, there are some drawbacks with histogram equalization [8] especially when implemented to process digital images.…”

Exact global histogram specification optimized for structural similarity

“…Image (contrast) enhancement ( [12], [14], [17][18][19]) is a traditional usage of histogram equalization (i.e., EHS with flat target histogram). By applying histogram equalization, the same number of pixels is -4 -assigned to each and every possible intensity level.…”

Adaptive Sigmoid Function to Enhance Low Contrast Images

“…Most of the contrast enhancement methods can be classified into two main categories: intensitybased techniques and feature-based techniques. Intensity-based methods can be expressed by the form I0(x, y) = f (I (x, y)) (1) where I (x, y) is the original image, I0(x, y) is the output image after enhancement, and f is a transformation function. In these methods, a transformation of the image gray levels is applied to the whole image such that the pixels with the same gray level at different places of the original image are still kept the same in the processed image.…”