Urban Features Identification from Dual-Pol SAR Images with Filter Properties

Abstract There is no formal definition of feature identification but it depends on the application and context of the problem. This feature acts as primary elements for execution of several algorithms, hence feature identification is one of the significant steps for has been very interesting for several research groups. Various researchers have attempted in this regard for feature identification. The current work presents an approach for urban feature identification from satellite datasets for a detailed analysis of the features for better management of the resources. Several features based feature extraction approach has been attempted to identify the compare with statistical profiling. Microwave remote sensing is one of the significant methods of remote sensing to get the data where our optical sensors usually failed or less capable to provide accurate and timely sensed data. In today’s world, active remote sensing is one of the greatest technologies which is used widely in many application areas. Synthetic aperture radar is the main object to get the actively remote sensed images. Either it’s optical or microwave data, the satellite images has its many errors, in SAR, while receiving the reflected echoes from the target the trouble has occurred in the form of Speckle Noise in an image. In this paper, the focus is on about the Speckle Noise, SLC & GRD data, the filtered images performance with Boxcar and Median filter, degraded and preserving information of an image, reduce speckle noise effect of an image.