Gaussian Noise Detection and Adaptive Non-local Means Filter
In this paper, a noise adaptive non-local means (NA-NLM) filter is presented to remove additive Gaussian noise from the corrupted images. Firstly, a novel pixel-wise Gaussian noise detection is proposed via eigen features of local Hessian matrix, and a metric is introduced to measure noise strength. Then, image denoising is performed by adaptive NLM filter according to the pixel-wise noise strength, i.e., the NLM filter varies adaptively with the size selections of the search window and similar patches. Experiments carried on Tampere Image Database (TID) demonstrate that the proposed method outperforms the state-of-the-art methods in terms of the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and subjective visual assessment.
This work was supported by the National Natural Science Foundation of China under Grant 61371190.
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