Investigation of Optimal Wavelet Techniques for De-noising of MRI Brain Abnormal Image

In the field of medical applications, typically obtained medical images like X-ray, CT, MRI etc. consists of noise that reduces the visual quality of an image. Therefore, de-noising is essential during the image acquisition process. Though several methods are available for de-noising the image, the performance metrics of wavelets and threshold values to be used are not optimized for assessing the quality of an image. In this paper, DWT techniques with suitable threshold value and five objective quality metrics are used for de-noising the abnormal MRI brain speckle noise image. Quality metrics like Squared Error Mean (SEM), Peak Signal to Noise Ratio (PSNR), Structural content (SC), Structural Similarity Index Method (SSIM), and Absolute Mean Error (AME) are estimated for de-noised MRI brain image are discussed. The quality of the image is assessed depending on the metrics and wavelet threshold techniques.