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NSCT Remote Sensing Image Denoising Based on Threshold of Free Distributed FDR
- Source :
- Procedia Engineering. 24:616-620
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- A new method for image denoising based on the free distributed hypothesis test threshold (FDR) and the non-sub-sampled contourlet transform(NSCT) is proposed in this paper. This method firstly acquires the free distributed false discovery rate hypotheses test in statistics to set the threshold in the NSCT domain, and then removes the noise through soft threshold function, which doesn’t depend on the length of signal. The experimental results show that the proposed method can more effectively reduce Gaussian noise and improve the peak value signal-to-noise ratio in the remote sensing image; Meanwhile, this method utilizes the shift invariant of NSCT transform to inhibit the pseudo Gibbs distortion effect, and integrally preserves the texture and edge etc.. details’ information of the image, thus obviously ameliorate the visual effect of the image.
- Subjects :
- False discovery rate
business.industry
Pattern recognition
General Medicine
Threshold function
Contourlet
symbols.namesake
Gaussian noise
symbols
Computer vision
Peak value
Artificial intelligence
Invariant (mathematics)
Image denoising
business
Engineering(all)
Statistical hypothesis testing
Remote sensing
Mathematics
Subjects
Details
- ISSN :
- 18777058
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- Procedia Engineering
- Accession number :
- edsair.doi.dedup.....dabbd19d61ee25ea242ef0006f5cba17
- Full Text :
- https://doi.org/10.1016/j.proeng.2011.11.2705