PolSAR Image Speckle Reduction Based on Classification of Similarity Features Between Coherency Matrices

Ping Han,Kun Jia,Binbin Han,Fei Dong

doi:10.1109/access.2019.2941223

Ping Han, Kun Jia + Show 2 more

Open Access

https://doi.org/10.1109/access.2019.2941223

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Abstract

A novel PolSAR image speckle reduction algorithm based on a new definition of similarity coefficient is proposed in this paper. Pixels in image are firstly classified into three types by threshold segmentation which is calculated with the similarity features. Then, weighted filtering is applied on the pixels selected according to their types, power features and similarity properties. Experimental results with measured data collected by NASA/JPL AIRSAR system show that the proposed method is more effective than Lee Filter not only in speckle suppression but also in polarimetric properties and structure feature preservation.

Highlights

In recent years, the application of Polarimetric Synthetic Aperture Radar (PolSAR) has been increasing in many fields such as marine exploration, crops monitoring, disaster assessment [1]–[5]
The filtering idea is same as Lee Filter, but here, we introduce R and threshold segmentation to do the classification and filtering pixel selection on a de-orientated image
In this paper, PolSAR image speckle reduction is performed based on the classification of similarity coefficients feature and good results are achieved

Summary

Introduction

The application of Polarimetric Synthetic Aperture Radar (PolSAR) has been increasing in many fields such as marine exploration, crops monitoring, disaster assessment [1]–[5]. The inherent speckle noises exist in PolSAR image reduce the signal-to-noise ratio and cover up the real features of the image, which affect its application seriously. Speckle suppression is an important research topic in PolSAR image interpretation. The most representative and widely used PolSAR image speckle filter is Lee Filter proposed by J. S. Lee [6], which is based on Freeman decomposition and classification with scattering characteristics of target. Beside its good filtering properties, Lee Filter has good polarization retention characteristics. (2) The application of Freeman decomposition is based on the assumption of reflection symmetry of ground If the polarimetric decomposition is performed directly on the original data, misclassification could be introduced. (2) The application of Freeman decomposition is based on the assumption of reflection symmetry of ground

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Results

Conclusion