Ms. Dolonchapa Prabhakar Profile

Dolonchapa Prabhakar

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Proceedings Article | 19 October 2023 Presentation + Paper

Image pre-processing and shadow detection for building extraction from high-resolution satellite images

Dolonchapa Prabhakar, Pradeep Kumar Garg

Proceedings Volume 12735, 1273508 (2023) https://doi.org/10.1117/12.2678670

KEYWORDS: Shadows, Light sources and illumination, Image processing, Color, RGB color model, Image segmentation, Earth observing sensors, Satellites, Satellite imaging, Image enhancement

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High resolution satellite imageries frequently contain shadows because of high-rise structures, especially in urban areas. One of the notable flaws in remotely sensed imaging that prevents information extraction is shadow. Building detection depends on the recognition of shadowy areas since they indicate a building's presence. Therefore, we can determine the structures' shapes and heights by utilizing the sun's illumination direction. But more crucially, detecting building shadows in high-resolution images can aid in better building detection. This work presents a shadow detection approach from a single RGB image to reduce the shadow effects on high-resolution images. We used LAB color space, which has one luminance (L) channel and two-color channels (A and B). To generate the buffer zone for building extraction, we transformed the RGB images to the CIELab color space to acquire the shadow masks. The proposed algorithm must be pre-processed to separate each shadow area into a separate data matrix to expand its functionality, evaluate the effectiveness of the method, and produce more accurate results when building shadows are close to one another. Additionally, by grouping the shadow zones into independent matrices, the method enables the detection of two or more distinct shadows of buildings with complex geometries and many parts in separate zones. Pre-processing helps us to prepare the images for further analysis. Using image pre-processing wisely, one can offer advantages and address issues that ultimately improve local and global feature detection. The effectiveness of building extraction and the outcomes of image analysis both dramatically improved results by image pre-processing.

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