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X-Ray Image Enhancement Using CLAHE Method
Sarthak Hailakar1, Sanket Godase2, Abhishek Laygude3, Prof. P.A.Bhor4
1 Sarthak Hailkar, sarthakhailkar@gmail.com ,JCOE Kuran
2 Sanket Godase, sanketgodse059@gmail.com,JCOE Kuran
3Abhishek Laygude, abhilaygude@gmail.com, JCOE Kuran
Prof.P.A.Bhor, Department of computer engineering, JCOE Kuran, Maharashtra, India
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Abstract Contrast Enhancement is one of the most significant techniques for increasing the standard of medical images since it allows for better visualisation and thus more accurate diagnosis. Its main goal is to eliminate the use of contrast material during the MRI scan method and compare the results of the metrics MSE, PSNR, AMBE, and contrast. When the contrasted nature of the image vary across the image, the histogram equalization (HE) approach is unsuccessful. Automatic Histogram Equalization (AHE) circumvents this issue by taking into account and increasing the mapping for each pixel in the histogram during a subsequent frame. CLAHE is another viable option. It prevents over-enhancing of noise and lowers the sting shadowing effect of limitless AHE by limiting enhancement to relatively uniform parts of the image. The contrast of their parameters is executed after the image has been enhanced using AHE and CLAHE. The goal is to provide tissue contrast that is optimised for each treatment location, allowing for precise patient daily treatment setup and, as a result, offline review. The advanced technique uses an image processing filter chain that includes a noise reduction filter, a high pass filter, and a CLAHE filter to handle 2D x-ray pictures.
Key Words- Normalization, Histogram Equalization, Contrast Limited Adaptive Histogram Equalization (CLAHE), Cumulative Distribution Function (CDF).