Identifikasi Objek pada Citra Thorax X-Ray Pasien COVID-19 dengan Metode Contrast Limited Adaptive Histogram Equalization (CLAHE) - Dodi Andre Putra; Jufriadif Na` am; Yuhandri (Jurnal Informasi dan Teknologi, 2022)
Chest X-Ray radiography produces digital radiographic images of the chest area such as the lungs, heart, and ribs. This image can visualize the lung condition of COVID-19 patients. Examination of the lung condition of COVID-19 patients with X-Ray is easier, cheaper, and widely available in hospitals than other radiographic techniques. However, the results of the X-Ray radiography digital image have poor quality, so they need to be improved. Low image contrast is a factor in the difficulty of identifying thorax images of COVID-19 patients. Increase the contrast of the low thorax image of COVID-19 patients with Contrast Limited Adaptive Histogram Equalization (CLAHE) so that it is easier to observe concretely and more clearly. The images that were processed in this study were 100 thorax images of COVID-19 patients sourced from the radiology department of Bhayangkara Hospital, Padang Indonesia. Furthermore, the image is processed using digital image processing using Matlab software. The processing stages of the thorax image are converted into grayscale form. The resulting grayscale image is continued with contrast processing using the CLAHE method with Uniform, Rayleigh and Exponential distribution types. The calculation of the Peak Signal to Noise Ratio (PNSR) and Mean Square Error (MSE) values of the image results from the processing of each type of CLAHE was continued. The results of testing all images can be visually improved in contrast quality. The average MSE CLAHE Uniform, Rayleigh and Exponential results were 27.68, 25.86 and 26.33, respectively. The average values of CLAHE Uniform, Rayleigh and Exponential PNSR > 30 dB are 112.32 dB, 171.95 dB and 151.90 dB, which means the CLAHE image is similar to the original image. CLAHE Rayleigh gives the best results in terms of quality and quantity with a total of 85 images or an accuracy value of 85%, while CLAHE Exponential and CLAHE Uniform are 15% and 0%, respectively.