Shift invariant properties of the dual-tree complex wavelet transform
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
Dual-tree Complex Wavelets Transforms for Image Denoising
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01
Wavelet Based Image Denoising Using Adaptive Thresholding
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
Image denoising with neighbour dependency and customized wavelet and threshold
Pattern Recognition
De-noising by soft-thresholding
IEEE Transactions on Information Theory
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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.