Enhancement of images with speckle noise reduction using different filters

TLDR: In this paper, a number of filters such as Lee Filter, Frost Filter, Kuan Filter, Weiner Filter, Median Filter and SRAD (Speckle Reducing Anistrophic Diffusion) Filter are applied to the following images such as Photographic, Ultrasound, SAR, PET, CT and MRI.

Abstract: An Image is often corrupted by noise in its acquisition and transmission. Noise is any undesired information that contaminates an image. Speckle or Multiplicative noise, is a signal-dependent form of noise, whose magnitude is related to the value of the original pixel. This tends to reduce the image resolution and contrast. Denoising speckle is one of the most important process to increase the quality of the image. Many filters are widely used to improve the quality of images by despeckling it. This work comprises a number of filters such as Lee Filter, Frost Filter, Kuan Filter, Weiner Filter, Median Filter and SRAD(Speckle Reducing Anistrophic Diffusion) Filter that are applied to the following images such as Photographic, Ultrasound, SAR, PET, CT and MRI. The Statistical measures such as Signal to Noise Ratio (SNR), Peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE), Root Mean Square Error (RMSE) are used to calculate the filtered images and the results are tabulated. These parameters are used to analyze image quality of the filtered images. The results obtained from the statistical measures are used for comparative study and also used to determine the filter name that is well suited for a particular type of image. The results obtained are presented in the form of statistical tables and graphs. Finally the best filter has been proposed based on the statistical and experimental results.