Image Preprocessing by Applying Filtering and Enhancement to Improve the Quality of the Computer Tomography (CT) Lung Image

One of the country's most severe and deadly diseases is lung disease. A prompt diagnosis and care can save lives. Despite being the best imaging tool in the medical sector, clinicians find it challenging to interpret and definitively diagnose from Computer Tomography (CT) scanning data. As a result, computer-assisted diagnostics can be helpful for clinicians in identifying malignant cells precisely. Despite numerous image denoising techniques over the decades, removing noise from a chaotic CT is still tricky without compromising the diagnostic features. Discrete Wavelet Transform (DWT) is one of the picture denoising methods with the most potential. However, the fundamental issue with wavelet thresholding is the softening of edges. An Image Filtering and Enhancement Model for Computed Tomography Lung Images (IFEM-CTLI) is suggested in this article to process the CT image. The image features are enhanced using the 2D Edge Preservation Histogram Improvement(2D-EPHI) method. The suggested system used 2D Hybrid Wavelet Frequency Domain Bilateral Filter (HWFDBF) for filtering and 2D-EPHIfor image enhancement. The simulation outcomes show the lower Root Mean Squared Error (RMSE) and higher Peak Signal to Noise Ratio (PSNR) of the proposed IFEM-CTLI with a hybrid filtering system and image enhancement model.