Noise removal plays vital role in image processing and also important pre processing task before performing post operation like Image segmentation etc.. This paper presents a effective and efficient algorithm in order to remove impulse noise from gray scale and color images. Challenging results show the superior performance of the proposed filtering algorithm compared to the other standard algorithms such as Standard Median Filter (SMF), Median Filter (MF), Weighted Median Filter (WMF) and Trimmed Median Filter (TMF). Furthermore, various performance metrics such as the MSE, PSNR and SSIM have been compared with Existing standard algorithms. The computational time for the denoised image is calculated for different noise levels and the proposed algorithm has lower computational time, hardware complexity and ease in operation.The obtained results prove that it has better qualitative analysis by improving visual appearance and challenging quantitative measures even at high noise densities ranging up to 90%.
General Terms
Impulse noise removal technique
KeywordsImpulse noise, Median filter, Peak signal to noise ratio, Mean square error, Salt and pepper noise, Structural similarity index metric.
Over the past four decades, the Synthetic Aperture Radar (SAR) imagery has become a beneficial and important application over the optical satellite imagery because of its ability to operate in any weather conditions. However, these images are affected with granular noise termed as Speckle noise. This noise affects the overall quality of the image adversely and hence hinders the observation of vital and crucial information present in the image. Thus, it has become essential to remove this speckle noise using suitable techniques. This paper presents the various important techniques available till date for the removal of speckle noise from SAR images and each technique with its own advantages and limitations are described. It also presents qualitative and quantitative measures of various techniques.
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