Detecting variable source areas from temporal radar imagery using advanced image enhancement techniques
- Author
- Aleksandra Pizurica (UGent) , Niko Verhoest (UGent) , Wilfried Philips (UGent) and François De Troch (UGent)
- Organization
- Abstract
- Recently, [1] showed that it is possible to map variable source areas in a catchment using a principal component analysis. This technique, based on a temporal series of images, revealed the spatial soil moisture patterns from the vegetation and topographic effects introduced in a Synthetic Aperture Radar (SAR) image. However, the obtained image is still corrupted with noise, which is partially related to the speckle observed within a SAR image. In order to get a noiseless image, which is more appropriate for hydrological modelling schemes, we apply a recently developed Wavelet-based image denoising technique [2]. The main advantage of this filtering technique is that it preserves the spatial patterns and observed edges, while it increases the signal to noise ratio significantly. The suitability of this denoising algorithm is investigated by comparing the hydrologic information included in these visually well-appearing images with the results obtained for their non-filtered counterparts.
- Keywords
- SINGULARITY DETECTION
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-401890
- MLA
- Pizurica, Aleksandra, et al. “Detecting Variable Source Areas from Temporal Radar Imagery Using Advanced Image Enhancement Techniques.” IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), edited by TI Stein, IEEE, 2000, pp. 2035–37, doi:10.1109/IGARSS.2000.858258.
- APA
- Pizurica, A., Verhoest, N., Philips, W., & De Troch, F. (2000). Detecting variable source areas from temporal radar imagery using advanced image enhancement techniques. In T. Stein (Ed.), IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) (pp. 2035–2037). https://doi.org/10.1109/IGARSS.2000.858258
- Chicago author-date
- Pizurica, Aleksandra, Niko Verhoest, Wilfried Philips, and François De Troch. 2000. “Detecting Variable Source Areas from Temporal Radar Imagery Using Advanced Image Enhancement Techniques.” In IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), edited by TI Stein, 2035–37. New York, NY, USA: IEEE. https://doi.org/10.1109/IGARSS.2000.858258.
- Chicago author-date (all authors)
- Pizurica, Aleksandra, Niko Verhoest, Wilfried Philips, and François De Troch. 2000. “Detecting Variable Source Areas from Temporal Radar Imagery Using Advanced Image Enhancement Techniques.” In IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), ed by. TI Stein, 2035–2037. New York, NY, USA: IEEE. doi:10.1109/IGARSS.2000.858258.
- Vancouver
- 1.Pizurica A, Verhoest N, Philips W, De Troch F. Detecting variable source areas from temporal radar imagery using advanced image enhancement techniques. In: Stein T, editor. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS). New York, NY, USA: IEEE; 2000. p. 2035–7.
- IEEE
- [1]A. Pizurica, N. Verhoest, W. Philips, and F. De Troch, “Detecting variable source areas from temporal radar imagery using advanced image enhancement techniques,” in IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), Honolulu, HI, USA, 2000, pp. 2035–2037.
@inproceedings{401890, abstract = {{Recently, [1] showed that it is possible to map variable source areas in a catchment using a principal component analysis. This technique, based on a temporal series of images, revealed the spatial soil moisture patterns from the vegetation and topographic effects introduced in a Synthetic Aperture Radar (SAR) image. However, the obtained image is still corrupted with noise, which is partially related to the speckle observed within a SAR image. In order to get a noiseless image, which is more appropriate for hydrological modelling schemes, we apply a recently developed Wavelet-based image denoising technique [2]. The main advantage of this filtering technique is that it preserves the spatial patterns and observed edges, while it increases the signal to noise ratio significantly. The suitability of this denoising algorithm is investigated by comparing the hydrologic information included in these visually well-appearing images with the results obtained for their non-filtered counterparts.}}, author = {{Pizurica, Aleksandra and Verhoest, Niko and Philips, Wilfried and De Troch, François}}, booktitle = {{IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)}}, editor = {{Stein, TI}}, isbn = {{9780780363595}}, keywords = {{SINGULARITY DETECTION}}, language = {{eng}}, location = {{Honolulu, HI, USA}}, pages = {{2035--2037}}, publisher = {{IEEE}}, title = {{Detecting variable source areas from temporal radar imagery using advanced image enhancement techniques}}, url = {{http://doi.org/10.1109/IGARSS.2000.858258}}, year = {{2000}}, }
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