Title :
Noise Invalidation Denoising
Author :
Beheshti, Soosan ; Hashemi, Masoud ; Zhang, Xiao-Ping ; Nikvand, Nima
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
Abstract :
A denoising technique based on noise invalidation is proposed. The adaptive approach derives a noise signature from the noise order statistics and utilizes the signature to denoise the data. The novelty of this approach is in presenting a general-purpose denoising in the sense that it does not need to employ any particular assumption on the structure of the noise-free signal, such as data smoothness or sparsity of the coefficients. An advantage of the method is in denoising the corrupted data in any complete basis transformation (orthogonal or non-orthogonal). Experimental results show that the proposed method, called noise invalidation denoising (NIDe), outperforms existing denoising approaches in terms of mean square error (MSE).
Keywords :
mean square error methods; signal denoising; confidence region; data smoothness; general-purpose denoising; mean square error; noise invalidation denoising; noise order statistics; noise signature; Additive noise; Colored noise; Gaussian distribution; Noise reduction; Random processes; Sorting; Confidence region; order statistics; thresholding;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2010.2074199