Study of the Preprocessing Influence in the Accuracy of Semi-automated Shadow Detection Approach

Shadows may occupy a significant portion of the image mainly in urban scenes. This research has the objective to detect shadows in high resolution orbital images using morphological operators. In order to verify preprocessing contribution in this shadow detection methodology, we have tested the median, morphological, bilateral and mean curvature filters to evaluate which one has the characteristic of mitigate the noise of the images and contribute to enhance detection performance. During the study, 10 panchromatic images of Worldview II satellite from the urban area of Presidente Prudente, in the state of Sao Paulo, were used. According to the shadow detection methodology by mathematical morphology, we checked the accuracy value using the images resulting of the smoothing methods applied in the preprocessing step. Finally, we evaluated all the smoothing levels in order to select the most appropriated according to accuracy and if images preserves the elements of interest. By analyzing the obtained results it is easy to see that the bilateral filter has presented satisfactory results, since it considers the spatial domain in the smoothing process, despite incorporating the pixels intensity domain as well. Therefore, we can conclude that the bilateral filter is a good alternative considering an adequate choice of the parameters.