Fast method for noise level estimation and integrated noise reduction

This paper describes a fast method for noise level estimation and denoising. Specifically, we address the problem of estimating the standard deviation of additive white Gaussian noise in digital images; the computed value is used to reduce Gaussian noise and eliminate defective pixels in a raw digital image. The method is particularly suitable for implementation in low power mobile devices with imaging capabilities such as camera phones, as well as digital still cameras (DSC).

[1]  Søren Ingvor Olsen Noise Variance Estimation in Images , 1993 .

[2]  Sebastiano Battiato,et al.  A noise reduction filter for full-frame data imaging devices , 2003, IEEE Trans. Consumer Electron..

[3]  Ossi Kalevo,et al.  Noise reduction techniques for Bayer-matrix images , 2002, IS&T/SPIE Electronic Imaging.

[4]  Sebastiano Battiato,et al.  Adaptive Temporal Filtering For CFA Video Sequences , 2003 .

[5]  Gian Antonio Mian,et al.  Statistical characteristics of granular camera noise , 1994, IEEE Trans. Circuits Syst. Video Technol..

[6]  Sebastiano Battiato,et al.  A temporal noise reduction filter based on image sensor full-frame data , 2003, 2003 IEEE International Conference on Consumer Electronics, 2003. ICCE..

[7]  Aggelos K. Katsaggelos,et al.  Noise reduction filters for dynamic image sequences: a review , 1995, Proc. IEEE.

[8]  Amar Mitiche,et al.  Reliable and fast structure-oriented video noise estimation , 2002, Proceedings. International Conference on Image Processing.