NIT Rourkela

Seminar Title

Modelling of Heterogeneous SAR Clutter for Speckle Suppression using MAP Estimation

Seminar Type

Synopsis Seminar

Department

Electronics and Communication Engineering

Speaker Type

Student

Speaker Name

Dheeren Ku Mahapatra

Date & Time

16 Jul 2018 5:15 PM

Venu

Room No. EC-138, ECE Dept. (Electrical Science Building)

Contact

Prof U K Sahoo

Abstract

Synthetic Aperture Radar (SAR) is an active high resolution imaging system that has been used intensively in diverse applications such as surveillance, environmental monitoring, urban planning, agriculture assessment etc. However, coherent nature of the SAR imaging system makes it highly susceptible to a multiplicative granular effect known as ‘Speckle’. The inherent presence of such speckle results in significant loss of relevant information, which in turn makes interpretation and also, processing of SAR data difficult to human interpreters as well as systems devised for computer vision. Moreover, the accuracy of most of the SAR image processing applications such as segmentation, classification, detection and recognition is also severely effected by such granular speckle. Consequently, speckle suppression (despeckling) is regarded as a crucial preprocessing step in various SAR imaging applications. Therefore, development of efficient despeckling filters has become the focal point of exploration for the researchers from radar community in recent years. A multitude of despeckling approaches has been developed so far, amongst which maximum-a-posteriori (MAP) based despeckling has earned utmost importance, since its simplicity in structure and practicability of implementation are found attractive apart from its accuracy in speckle suppression. However, the state-of-the-art MAP filters are not sufficiently effective in simultaneous mean preservation and speckle suppression from clutter data with varying degree of heterogeneity. Such inefficacy is due to (i) inability of corresponding clutter models in portraying statistics of both moderately heterogeneous and extremely heterogeneous areas, (ii) inaccurate estimation of clutter model parameters, (iii) mathematically intractable expression for the clutter probability density function (pdf) and/or its associated parameter estimates. In order to address the challenges in devising MAP based filters for despeckling clutter with varying degree of heterogeneity, work presented in this dissertation focuses to find mathematically tractable generalised clutter models. The clutter models are proposed along with the corresponding estimators for obtaining model parameters. The analytical as well as experimental assessment on validity and applicability of the models are elaborately discussed.

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