Image enhancement in spatial domain: A comprehensive study

With the advancement of imaging science, image enhancement has become an important aspect of image processing domain. It is necessary to gather a comprehensive knowledge regarding the existing enhancement technologies to identify and solve their problems and thus to elevate the current image enhancement methodologies. This paper provides the underlying concept of contrast enhancement, brightness preservation as well as brightness enhancement techniques. Besides this, we provide a short description of the existing renowned enhancement methods with their mathematical description and application area. Moreover, experimental results are provided to make a comparative analysis where both qualitative and quantitative measurements are performed. Different enhancement methods are run on same images to examine the qualitative performance. Peak signal to noise ratio (PSNR), normalized cross-correlation (NCC), execution time (ET) and discrete entropy (DE) are quantitative measurement metrics used for quantitative assessment. Most of the cases, it is found that Histogram Equalization has the highest degree of deviation from the input image which basically generates more visual artifacts. Contextual and Variational Contrast enhancement technique takes long time for execution with respect to other enhancement techniques. From our quantitative and qualitative evaluation, we find that Layered Difference Representation performs comparatively produces better enhancement result in all aspect than other existing methods.