Abstract
ABSTRACTThe speckle noise of synthetic aperture radar (SAR) images limits its application in change detection. Compared with improved ratio (IR) and log-ratio (LR) operators, the neighborhood-based ratio (NR) technique can restrain the influence of speckle noise and is more suitable for change detection in SAR images. However, we find three drawbacks of NR by analyzing this method carefully. To overcome these defects, we propose an improved neighborhood-based ratio (INR) approach for change detection in SAR images. INR restructures the NR operator to exploit the neighborhood information more reasonably and is expected to reduce the impact of speckle noise better. IR, LR, mean ratio operator, NR, and INR are tested on two data sets to compare their performances in change detection of SAR images. Experimental results show that the proposed method can obtain better difference image than other state-of-art methods and improve the accuracy of change detection in SAR images effectively.
Highlights
Change detection is a technique to detect the land cover changes that have occurred in the investigated area by using remote sensing images acquired in the same geographical area at two different dates (Bruzzone & Prieto, 2000)
The difference image acquired with the proposed approach performs best because improved neighborhood-based ratio (INR) reasonably exploits heterogeneity measurement to balance between restraining speckle noise and preserving the details of synthetic aperture radar (SAR) image
The difference image acquired with INR, whose receiver operating characteristic (ROC) curve is closer to the upper left corner, performs best because INR reasonably exploits the neighborhood information of SAR images
Summary
Change detection is a technique to detect the land cover changes that have occurred in the investigated area by using remote sensing images acquired in the same geographical area at two different dates (Bruzzone & Prieto, 2000). On the basis of IR, mean ratio (MR) operator, employing the local mean information of SAR images to restrain the impact of speckle noise, was reported for change detection in SAR images (Ma, Gong, & Zhou, 2012). The neighborhood-based ratio (NR) method was proposed to change detection of SAR images (Gong, Cao, & Wu, 2012). This method employs heterogeneity of the local area, widely used in auto-adaptive filter algorithms (Argenti & Alparone, 2002; Lopes, Touzi, & Nezry, 1990), to control the influence weight of the neighborhood information to the center pixel.
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