Optimized Solution for Object based Segmentation and Shadow Removal using Remote Sensing Images
| Main Author: | V. Kovendan |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3764464 |
Daftar Isi:
- In the last 15 years there was a big analysis need on high resolution images for all the application areas such as medical field, security system and also remote sensing images. The remote sensing image plays the major role in the image processing which needs the high quality of the image for different applications. However processing the surface features are much complex with different kinds of objects and the shadow formation with the acquired images such as high rising buildings and other obstacles around the images. These can be processed by the modernization using 3D, position recognition but also they can obstruct with the processing of the remote sensing images. Detection and the image classification is the major resource of urban remote sensing images. In this paper, the urban high-resolution remote sensing images are subjected to shadow detection and removal process done in order to obtain a clear image. The shadow detection process is performed using segmentation and the shadow removal is performed using IOOPL matching and a clear image is retrieved using the classification algorithms.