TY  - CONF
TI  - Speckle noise filtering based on signal subspace technique
ID  - scholars3140
SP  - 168
KW  - Artificial intelligence; Signal analysis; Speckle; Synthetic aperture radar
KW  -  Anisotropic diffusion filters; Blurring effect; Image distortions; Noise subspace; Noisy image; Residual noise; SAR Images; Signal sub-space; Signaltonoise ratio (SNR); Simulated images; Speckle noise; Speckle noise reduction; Spectral components
KW  -  Signal to noise ratio
N2  - In this paper, a subspace-based technique for speckle noise reduction in images is proposed. The method is based on a linear model obtained by minimizing the energy of image distortion while keeping the energy of the residual noise in each spectral component below some given threshold. Image enhancement is achieved by removing the noise subspace and estimating the clean signal from the remaining signal subspace. The performance of the proposed approach is tested with simulated images and real SAR images, and compared with Lee and homomorphic anisotropic diffusion filters. The results indicate that the proposed technique increases the signal-to-noise ratio (SNR) by 3.6dB to 5.7dB over the noisy image. In addition, the proposed SDC algorithm is better at preserving the fine texture and introduces less blurring effect into the denoised image. © 2012 IEEE.
N1  - cited By 0; Conference of 2012 1st IEEE International Conference on Computational Intelligence and Cybernetics, CyberneticsCom 2012 ; Conference Date: 12 July 2012 Through 14 July 2012; Conference Code:95862
AV  - none
CY  - Bali
EP  - 174
A1  - Yahya, N.
A1  - Kamel, N.S.
A1  - Malik, A.S.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874561131&doi=10.1109%2fCyberneticsCom.2012.6381640&partnerID=40&md5=aaf36ecdbecd37869efaaa99fc67749a
PB  - IEEE Computer Society
SN  - 9781467308922
Y1  - 2012///
ER  -