Back to Search
Start Over
A COMPLEX SPECTRUM BASED SAR IMAGE RESAMPLING METHOD WITH RESTRICTED TARGET SIDELOBES AND STATISTICS PRESERVATION
- Source :
- IGARSS, IGARSS, Jul 2017, Fort-Worth, United States, 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017 IEEE International Geoscience and Remote Sensing Symposium, Jul 2017, Fort Worth, United States. ⟨10.1109/IGARSS.2017.8128214⟩
- Publication Year :
- 2017
- Publisher :
- HAL CCSD, 2017.
-
Abstract
- International audience; The aim of this work is to present a resampling scheme for SAR images that preserves spatial resolution and produces statistically accurate images at the same time. Indeed, SAR images are, for reasons due to their acquisition process, well sampled signals according to the Shannon sampling theory. In the presence of strong responses, that we will refer to as targets, a sinc-like function centered at the target is smeared over the entire image and is particularly visible in the range of tens of pixels surrounding the target. To mitigate this phenomenon, the usual solution is to apply an apodization window in the Fourier domain so as to change the cardinal sine impulse response into a much rapidly decaying one. This approach has two major drawbacks. It reduces the resolution of the image and introduces inaccurate statistical dependency between pixels. We propose to resample the image in an adaptive and robust way so that the target smear is canceled and the new sampled image is completely faithful to the underlying signal.
- Subjects :
- Computer science
0211 other engineering and technologies
Shannon interpolation
02 engineering and technology
[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Apodization
Robustness (computer science)
Resampling
0202 electrical engineering, electronic engineering, information engineering
Image scaling
Image resolution
Impulse response
ComputingMilieux_MISCELLANEOUS
021101 geological & geomatics engineering
Pixel
business.industry
complex spectrum
subpixellic image processing
Pattern recognition
total variation
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]
Computer Science::Computer Vision and Pattern Recognition
Frequency domain
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
targets
020201 artificial intelligence & image processing
Artificial intelligence
business
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- IGARSS, IGARSS, Jul 2017, Fort-Worth, United States, 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017 IEEE International Geoscience and Remote Sensing Symposium, Jul 2017, Fort Worth, United States. ⟨10.1109/IGARSS.2017.8128214⟩
- Accession number :
- edsair.doi.dedup.....26bfc474244bcecc2019fcb0be5abd71
- Full Text :
- https://doi.org/10.1109/IGARSS.2017.8128214⟩