Automated Intensity Manipulation Using Histogram Matching For 2D-Image
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Contrast enhancement is an important factor in the image preprocessing step. One of the widely accepted contrast enhancement method is the histogram Matching. The overall aim of this project is to develop scheme for intensity Manipulation using Histogram Matching to match an image histogram with another targeted image histogram. The tools that were used for the development of the scheme include gray scale two-dimensional images, and MATLAB simulation environment. Histogram Matching is a simple and effective image enhancement technique. It tend to change the brightness of an image according to ...
Contrast enhancement is an important factor in the image preprocessing step. One of the widely accepted contrast enhancement method is the histogram Matching. The overall aim of this project is to develop scheme for intensity Manipulation using Histogram Matching to match an image histogram with another targeted image histogram. The tools that were used for the development of the scheme include gray scale two-dimensional images, and MATLAB simulation environment. Histogram Matching is a simple and effective image enhancement technique. It tend to change the brightness of an image according to specified histogram by about 80%. Histogram equalization on the other hand it tends to change the mean brightness of the image to the middle level of the permitted range by approximately 50%, and hence is not a very suitable for some applications. To preserve brightness and to enhance contrast of images, numerous methods are introduced, but many of them present unwanted artifact such as intensity saturation, over-enhancement and noise amplification. In the present research, available image quality measurement such as Structural Similarity Index (SSIM) based methods are reviewed.
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