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Speckle Noise Reduction And Quality Enhancement of Images Using Different Filters



Noise can be introduced into the image during the image acquisition and transmission process. Noise in images is the necessary factor which degrades the quality of the images. Speckle or multiplicative noise, is a form of noise often dependent on the signal, where the amplitude is attached to the value of the original pixel. This tends to minimize the contrast and resolution of the image. In order to increase the quality of the image, we must minimize the speckle noise. For this, several filters are used to reduce the noise and consequently improve the quality of the images. This paper compares the effectiveness of different speckle reduction filters such as Frost Filter, Lee Filter, Kuan Filter, Wiener Filter, Median Filter and SRAD (Speckle Reducing Anistrophic Diffusion) Filter, applied to the different type of images such as Synthetic Aperture Radar (SAR), Ultrasound, Computerized Tomography Scan (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Photographic. The statistical parameters such as Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE) and Root Mean Square Error (RMSE) are compared and the results are tabulated, which allows us to determine the suited filter that is well for the corresponding image type. Finally the best filter has been found and proposed based on the statistical and experimental results.


Speckle noise, Speckle Filtering, SAR, Ultrasound, PET, CT, Photographic, MRI Images, Statistical measures.

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