Multitemporal Sar Image Despeckling Based on Immse Filtering

Most multitemporal filtering techniques assume that pixels remain unchanged over the time so that all the pixels at the same position in the time series are averaged. However, this assumption is not suitable in a long-period time series. To overcome this problem, a novel approach for temporal filtering of SAR image time series by applying the iterative minimum mean square error (IMMSE) approach is proposed. Real and simulated time series data sets were tested. Results showed that the IMMSE preserved the temporal unchanged areas filtered and enhanced the blurred temporal changed details.

[1]  Luisa Verdoliva,et al.  Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Maoguo Gong,et al.  SAR Image Despeckling Based on Local Homogeneous-Region Segmentation by Using Pixel-Relativity Measurement , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Jean-Marie Nicolas,et al.  Adaptive Multitemporal SAR Image Filtering Based on the Change Detection Matrix , 2014, IEEE Geoscience and Remote Sensing Letters.

[4]  Yazdan Amerian,et al.  Speckle Noise Reduction of Time Series Sar Images Based on Wavelet Transform and Kalman Filter , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.