Application of Gaussian Filter and Histogram Equalization for Repair x-ray Image
Abstract
The X-ray image is a medical examination procedure that uses electromagnetic wave radiation to get a picture of the inside of the body. However, in the process, there is noise that appears due to the exposure factor. This research builds a system to improve the X-ray image with noise by using Gaussian Filter and Histogram Equalization. In this study, in order to see the optimization of image enhancement, the two methods were combined. The data used are 60 x-ray images that have noise and each has an original image without noise as a comparison image to get system accuracy using PSNR and SSIM. Gaussian Filter method is used to reduce noise by determining the size of the kernel matrix and the standard deviation used. Histogram Equalization method is used to even out the value of the gray level of the image. Based on the test results from the combination of the two methods, the larger the size of the kernel matrix used, the faster the duration of time needed to repair the image. The PSNR value and accuracy obtained in the X-ray image repair are 31 dB and 71% on a 3x3 kernel matrix with an average time duration of 9 seconds, 32 dB and 77% on a 5x5 kernel matrix with an average duration of 9 seconds, 32 dB and 78% on a 7x7 kernel matrix with an average time duration of 8 seconds
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