Abstract:
CT imaging is widely used in medical science over the last decades. The process of CT image reconstruction depends on many physical measurements such as radiation dose, software/hardware. Due to statistical uncertainty in all physical measurements in Computed Tomographythe inevitable noise is introduced in CT images.
Image enhancement is considered as one of the most important techniques in image research. The main aim of image enhancement is to enhance the quality and visual appearance of an image. Medical CT images suffer from poor and bad contrast and noise. It is necessary to enhance the contrast and remove the noise to increase image quality. One of the most important stages in medical images detection and analysis is Image Enhancement Techniques. It improves the clarity of images for human viewing, removing blurring and noise, increasing contrast, and revealing details.in this study four methods were used for enhancing brain computed tomography (CT) image, adaptive histogram equalization (AHE), adaptive subtraction and edge enhancement, on the other hand the forth method was combination between edge enhancement and wavelet decomposition, then lastly feature measurement PSNR ,MSE,NCC,AD,SC,MD,NAE and SSIMwere used to compared these four methods.
