Selection of Suitable Window Size for Speckle Reduction and Deblurring using SOFM in Polarimetric SAR Images

2015 ◽  
Vol 43 (4) ◽  
pp. 739-750 ◽  
Author(s):  
Sanjay Shitole ◽  
Shaunak De ◽  
Y. S. Rao ◽  
B. Krishna Mohan ◽  
Anup Das
Keyword(s):  
Window Size ◽  
Speckle Reduction ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Selection Of

Multi-Temporal Speckle Reduction of Polarimetric SAR Images: a Ratio-Based Approach

2019 ◽  
Author(s):  
Charles-Alban Deledalle ◽  
Loic Denis ◽  
Laurent Ferro-Famil ◽  
Jean-Marie Nicolas ◽  
Florence Tupin
Keyword(s):  
Speckle Reduction ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Multi Temporal

scholarly journals NON-LOCAL MEANS FILTER FOR POLARIMETRIC SAR SPECKLE REDUCTION-EXPERIMENTS USING TERRASAR-X DATA

2015 ◽  
Vol II-3/W4 ◽  
pp. 71-77 ◽  
Author(s):  
J. Hu ◽  
R. Guo ◽  
X. Zhu ◽  
G. Baier ◽  
Y. Wang
Keyword(s):  
Similarity Measures ◽  
Speckle Reduction ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Information Preservation ◽  
Local Means ◽  
Adaptive Weight ◽  
Non Local ◽  
The Impact ◽  
Intrinsic Characteristic

The speckle is omnipresent in synthetic aperture radar (SAR) images as an intrinsic characteristic. However, it is unwanted in certain applications. Therefore, intelligent filters for speckle reduction are of great importance. It has been demonstrated in several literatures that the non-local means filter can reduce noise while preserving details. This paper discusses non-local means filter for polarimetric SAR (PolSAR) speckle reduction. The impact of different similarity approaches, weight kernels, and parameters in the filter were analysed. A data-driven adaptive weight kernel was proposed. Combined with different similarity measures, it is compared with existing algorithms, using fully polarimetric TerraSAR-X data acquired during the commissioning phase. The proposed approach has overall the best performance in terms of speckle reduction, detail preservation, and polarimetric information preservation. This study suggests the high potential of using the developed non- local means filer for speckle reduction of PolSAR data acquired by the next generation SAR missions, e.g. TanDEM-L and TerraSAR-X NG.

scholarly journals AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

2016 ◽  
Vol XLI-B7 ◽  
pp. 611-615
Author(s):  
J. Q. Zhao ◽  
J. Yang ◽  
P. X. Li ◽  
M. Y. Liu ◽  
Y. M. Shi
Keyword(s):  
Change Detection ◽  
Detection Method ◽  
Speckle Noise ◽  
Natural Phenomena ◽  
Threshold Selection ◽  
Test Statistic ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Multi Temporal ◽  
Selection Of

Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

scholarly journals AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

2016 ◽  
Vol XLI-B7 ◽  
pp. 611-615 ◽  
Author(s):  
J. Q. Zhao ◽  
J. Yang ◽  
P. X. Li ◽  
M. Y. Liu ◽  
Y. M. Shi
Keyword(s):  
Change Detection ◽  
Detection Method ◽  
Speckle Noise ◽  
Natural Phenomena ◽  
Threshold Selection ◽  
Test Statistic ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Multi Temporal ◽  
Selection Of

Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

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