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Proceedings Paper

Quantum-inspired remote sensing image denoising with double density dual-tree complex wavelet transform
Author(s): Ying Zhang; Siwen Bi; Shuhui Wei
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Paper Abstract

Considering that Double-density dual-tree(DD-DT)complex wavelet has translation invariance, anti-aliasing properties and more compact space intervals, based on the quantum-inspired parameter estimation, this paper proposed a new quantum-inspired noise reduction method based on DD-DT complex wavelet transform for remote sensing images, especially the SAR images. The general process is addressed as below: conduct a logarithmic transformation for the SAR images, convert the multiplicative speckle noises to additive noises; then decompose the DD-DT complex wavelets for each image, thus to get the wavelet coefficient for each layer in all detailed directions; consider the inter-scale correlation of wavelet coefficient, utilize the Bayesian estimation theory along with the quantum mechanics principle of superposition, calculate the estimated wavelet coefficient; and then process the data layer by layer, refactor the SAR images using the processed coefficients. Then conduct a anti-logarithmic transformation to get the noise reduction result. Compare with the results of traditional methods, the resulting images have a significant improvement in different evaluation functions such as the Peak Signal Noise Ratio, Edge Preserve Index etc. The results have also shown better noise reduction quality in the images.

Paper Details

Date Published: 18 November 2014
PDF: 6 pages
Proc. SPIE 9299, International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications, 92990P (18 November 2014); doi: 10.1117/12.2072024
Show Author Affiliations
Ying Zhang, Institute of Remote Sensing and Digital Earth (China)
Siwen Bi, Institute of Remote Sensing and Digital Earth (China)
Beijing Institute of Space Mechanics and Electricity (China)
Shuhui Wei, Institute of Remote Sensing and Digital Earth (China)


Published in SPIE Proceedings Vol. 9299:
International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications
Anatoli G. Borovoi; Dong Liu, Editor(s)

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