  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).
