Image Processing) Linear stretching; Histogram equalization; and Histogram specification

In digital image processing, various techniques can be used to enhance the contrast of an image. Three common methods are linear stretching, histogram equalization, and histogram specification:

Linear stretching

Linear stretching, also known as normalization or contrast stretching, is a technique that improves the contrast of an image by redistributing the intensity values across the entire intensity range. It maps the minimum pixel value in the input image to 0 and the maximum pixel value to the highest value in the intensity range (usually 255 for 8-bit images), while linearly scaling the values in between. Linear stretching increases the contrast in images with narrow intensity ranges by stretching the pixel values over a wider range.

Histogram equalization

Histogram equalization is a more advanced contrast enhancement technique that redistributes the pixel values in an image so that the output image has a uniform histogram (i.e., equal frequency of occurrence for each intensity level). This method can be particularly useful for images with poor contrast due to uneven lighting or sensor limitations. Histogram equalization increases the global contrast of an image and makes hidden details more visible by spreading out the pixel values across the entire intensity range.

Histogram specification (or histogram matching)

Histogram specification is a technique that transforms the pixel values in an image so that its histogram matches a desired target histogram. This method can be used to standardize the appearance of images acquired under different conditions or to impose a specific histogram shape for aesthetic or other purposes. Histogram specification involves two main steps: first, perform histogram equalization on the input image; second, perform inverse histogram equalization on the equalized image using the target histogram.