Abstract
In the change detection application of remote sensing, commonly the variation in the brightness values of the pixels/objects in bi-temporal image is used as an indicator for detecting changes. However, there exist effects, other than a change in the objects that can cause variations in the brightness values. One of the effects is the illumination difference on steep surfaces mainly steeproofs of houses in very high resolution images, specifically in off-nadir images. This can introduce the problem of false change detection results. This problem becomes more serious in images with different view-angles. In this study, we propose a methodology to improve the building change detection accuracy using imagery taken under different illumination conditions and different view-angles. This is done by using the Patch-Wise Co-Registration (PWCR) method to overcome the misregistration problem caused by view-angle difference and applying Topographic Correction (TC) methods on pixel intensities to attenuate the effect of illumination angle variation on the building roofs. To select a proper TC method, four of the most widely used correction methods, namely C-correction, Minnaert, Enhanced Minnaert (for slope), and Cosine Correction are evaluated in this study. The results proved that the proposed methodology is capable to improve the change detection accuracy. Specifically, the correction using the C-correction and Enhanced Minnaert improved the change detection accuracy by around 35% in an area with a large number of steep-roof houses imaged under various solar angles.
Highlights
There are numerous papers published in the remote sensing literature for building change detection in which the intensity variation on the building roofs are taken as the change criterion since the roofs are more observable in the remote sensing images compared to other parts of the buildings
This is done by using the Patch-Wise Co-Registration (PWCR) method to overcome the misregistration problem caused by view-angle difference and applying Topographic Correction (TC) methods on pixel intensities to attenuate the effect of illumination angle variation on the building roofs
In dataset C1, there are few hachured buildings which means that the original brightness values were sufficient for change detection without any corrections due to the similar solar angles if the images
Summary
There are numerous papers published in the remote sensing literature for building change detection in which the intensity variation on the building roofs are taken as the change criterion since the roofs are more observable in the remote sensing images compared to other parts of the buildings. The MAD method uses a linear function to transfers the brightness values to another space in which the difference is highlighted [10] [11], while the non-linear approaches are based on the image histograms and the information content of the corresponding pixels [12]. In both cases, the variations in the brightness values play an important role in change detection. Other than changes, the variation of pixel brightness values in bi-temporal images depends as well on factors such as solar angles and topographic effects which cannot be comprehensively addressed by the linear or non-linear approaches
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