Adaptive threshold-based shadow masking for across-date settlement classification of panchromatic QuickBird images

Multitemporal land-use analysis is becoming increasingly important for the effective management of earth resources. Despite that, consistent differences in the viewing and illumination geometry in satellite-borne imagery introduce some issues in the creation of land-use classification maps. The focus of this study is settlement classification with high-resolution panchromatic acquisitions, using texture features to distinguish between settlement classes. The important multitemporal variance component of shadow is effectively removed before feature determination, which allows for minimum-supervision across-date classification. Shadow detection based on local adaptive thresholding is employed and experimentally shown to outperform existing fixed threshold shadow detectors in increasing settlement classification accuracy. Both same and across-date settlement accuracies are significantly improved with shadow masking during feature calculation. A statistical study was performed and found to support the hypothesis that the increased accuracy is due to shadow masking specifically.National Research Foundationhttp://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8859hb2014ai201

An approach for Shadow Detection and Removal based on Multiple Light Sources

Shadows in images are essential but sometimes unwanted as they can decline the result of computer vision algorithms. A shadow is obtained by the interaction of light with objects in an image surface. Shadows may letdown the image analysis processes and also cause a poor quality of information which in turn leads to problems in execution of algorithms. In this paper, a method has been proposed to detect and remove the shadows where multiple sources of light is been estimated, as we can take an example of playground stadium where multiple floodlights are fixed, multiple shadows can be observed originating from each of the targets. To successfully track individual target, it is essential to achieve an accurate image of the foreground. Also, an effort has been done to list some of the very crucial techniques related to shadow detection and removal. Many times, the shadow of the background information is merged with the foreground object and makes the process more complex. DOI: 10.17762/ijritcc2321-8169.150517

Adaptive Threshold-Based Shadow Masking for Across-Date Settlement Classification of Panchromatic QuickBird Images

Multitemporal land-use analysis is becoming increasingly important for the effective management of earth resources. Despite that, consistent differences in the viewing and illumination geometry in satellite-borne imagery introduce some issues in the creation of land-use classification maps. The focus of this study is settlement classification with high-resolution panchromatic acquisitions, using texture features to distinguish between settlement classes. The important multitemporal variance component of shadow is effectively removed before feature determination, which allows for minimum-supervision across-date classification. Shadow detection based on local adaptive thresholding is employed and experimentally shown to outperform existing fixed threshold shadow detectors in increasing settlement classification accuracy. Both same and across-date settlement accuracies are significantly improved with shadow masking during feature calculation. A statistical study was performed and found to support the hypothesis that the increased accuracy is due to shadow masking specifically.National Research Foundationhttp://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8859hb2014ai201