The problem considered here is the blind restoration of an image from noisy distorted samples, , where is an additive Gaussian noise, and an unknown, but parametrizable, linear operator. A typical distortion is the convolution with a Gaussian PSF of unknown width (atmospheric blur), or motion blur.
Our approach to this problem consists in, first, identifying the unknown parameters of the distortion, then in using a non-blind restoration algorithm; e.g., our multi-Wiener SURE-LET deconvolution algorithm, when the distortion is a convolution.
The estimation of the parameters involves the following ingredients:[1] Xue, F. & Blu, T.,"A Novel SURE-Based Criterion for Parametric PSF Estimation", IEEE Transactions on Image Processing, Vol. 24 (2), pp. 595-607, February 2015. |
[2] Xue, F. & Blu, T.,"SURE-Based Motion estimation", Proceedings of the IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC'12), Hong Kong, China, pp. 373-377, August 12--15, 2012. |
[3] Xue, F. & Blu, T.,"SURE-based blind Gaussian deconvolution", Proceedings of the IEEE Statistical Signal Processing Workshop (SSP), Ann Arbor, USA, pp. 452-455, August 5--8, 2012. |