Estimation of signal-dependent noise level function in transform domain via a sparse recovery model

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Jingyu YangChunping Hou

Abstract

This paper proposes a novel algorithm to estimate the noise level function (NLF) of signal-dependent noise (SDN) from a single image based on the sparse representation of NLFs. Noise level samples are estimated from the high-frequency discrete cosine transform (DCT) coefficients of nonlocal-grouped low-variation image patches. Then, an NLF recovery model based on the sparse representation of NLFs under a trained basis is constructed to recover NLF from the incomplete noise level samples. Confidence levels of the NLF samples are incorporated into the proposed model to promote reliable samples and weaken unreliable ones. We investigate the behavior of the estimation performance with respect to the block size, sampling rate, and confidence weighting. Simulation results on synthetic noisy images show that our method outperforms existing state-of-the-art schemes. The proposed method is evaluated on real noisy images captured by three types of commodity imaging devices, and shows consistently excellent SDN estimation performance. The estimated NLFs are incorporated into two well-known denoising schemes, nonlocal means and BM3D, and show significant improvements in denoising SDN-polluted images.

References

May 5, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Michael B WakinRichard G Baraniuk
Aug 11, 2007·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Kostadin DabovKaren Egiazarian
Dec 18, 2007·IEEE Transactions on Pattern Analysis and Machine Intelligence·Ce LiuWilliam T Freeman
Dec 9, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Mohammed Ghazal, Aishy Amer
May 30, 2012·IEEE Transactions on Pattern Analysis and Machine Intelligence·Radhakrishna AchantaSabine Süsstrunk

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Citations

Jun 14, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhi-Wei PanJohn H Xin

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