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Improvement in Image Denoising Technique Based on Dual-Tree Wavelet Transform and Multiresolution Local Contrast Entropy

Own H. S.

Machine Graphics and Vision

2010

Vol. 19, No. 2

143-157

The paper proposes an improvement in image denoising using Dual-Tree Complex Wavelet Transform (DT-CWT). Depending on the probability distribution of the noise in the wavelet coefficients, an adaptive threshold estimation algorithm is introduced. The threshold enables the proposed algorithm to adapt to unknown smoothness of the noisy images. The algorithm looks at the local contrast entropy of a complex wavelet coefficient instead of its magnitude in order to remove the noise from the image. Simulation results show improved performance of our image denoising method compared to other popular denoising algorithms, such as VisuShrink, Wiener2, ProbShrink, and our previous work based on DWT.