A Comparative Analysis of Speckle Noise Removal in SAR Images

The synthetic aperture radar images have a granular disturbance noise know as Speckle. The speckle is also called as a multiplicative noise. Over last few decades, various filters like lee, frost, wiener, mean and median filters are used and claimed to be efficient to reduce this granular noise present in SAR images. This process of removing speckles is also known as despeckling. The aim of this paper is to make a comparative review of despeckling methods. These methods will be used to highlight the trends and many approaches which changed over the years. This paper has discussed the technical aspects of the different filters and summarized it to use to remove the speckle in SAR images. Quantitative and qualitative parameters like mean, variance, edge saving index in horizontal & vertical, target to clutter ratio, equivalent number of looks have been analyzed and it concludes a method which uses different window sizes to reduce speckle in SAR images, which has efficient noise removal capabilities as compared with traditional methods like adaptive and non-adaptive filtering. It can extends to use of various machine learning algorithms to optimize the result towards betterment of different performance parameters.