A comparative study on wavelet denoising for high noisy CT images of COVID-19 disease

Gungor, Murat Alparslan

Coronavirus disease (COVID-19), detected in Wuhan City, Hubei Province, China, is a pandemic disease and affecting all people in the world. Real-time reverse transcription polymerase chain reaction (RT-PCR) test is the standard clinical tool for the diagnosis of COVID-19. Computed Tomography (CT) is an alternative method to RT-PCR test for the diagnosis of COVID-19 due to some disadvantages of the RT-PCR test. In this method, the target is to determine coronavirus pneumonia from CT images. However, high noise decreases the image quality, so a noise reduction filter is used. The wavelet functions are widely used to reduce noise in images. In this study, a performance comparison of the different wavelet functions in CT image denoising is proposed. Significant remarks are obtained from the analysis to improve the quality for CT exams of COVID-19 disease.