Digitization and Improvement of Lung X-ray Scan Display with WWW Filter and Histogram Equalization Method
Keywords:
Covid-19, PSNR, EME, WWW filter, Histogram equalizationAbstract
Detection of lung disease is generally done manually by trained professionals. The condition of pulmonary disorders has worsened since the outbreak of the 2019 coronavirus disease (COVID-19), which is a significant threat to people’s lives and health due to its high infectivity and rapid spread. Lung X-ray images are one way to detect various lung diseases and COVID-19 disorders. However, the image’s appearance is usually affected by pixels with uneven grayscale and isolated noise, making it weak in detecting the symptoms encountered. To solve this problem, a WWW filter method for preprocessing is proposed, as well as incorporating histogram equalization. In particular, histogram equalization is applied to increase the image’s contrast. The WWW filter combines wavelet, Wiener, and weighing methods to get a clear view of the lungs. The histogram process will provide a significant contrast value, making it easier for experts to further lung diagnosis. From the trial conducted, the PSNR value of 14.0931 to 19.9037 and an increase in EME from 23.1308 to 75.2877. The experimental results prove that the proposed algorithm can effectively detect pulmonary disease symptoms and is expected to be useful for diagnosing COVID-19.
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