Chinese Optics Letters, 2006, 4 (5): 05279, Published Online: Jun. 6, 2006
Speckle reduction algorithm for laser underwater image based on curvelet transform
110.4280 Noise in imaging systems 100.2980 Image enhancement 140.0140 Lasers and laser optics 100.7410 Wavelets
Abstract
Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.
Wei Ni, Baolong Guo, Liu Yang, Peiyan Fei. Speckle reduction algorithm for laser underwater image based on curvelet transform[J]. Chinese Optics Letters, 2006, 4(5): 05279.