A new method for removing salt-and-pepper noise from corrupted images is presented. We employ an efficient impulse noise detector based on the image sparse representation to detect the noisy pixels, and a local median filter to estimate the intensity values of noisy pixels. Experimental results demonstrate that the proposed method obtains better performance in terms of both qualitative and quantitative evaluations than those de-noising techniques such as the median filter, the peak-and-valley filter, the detail preserving filter, and the boundary discriminative noise detection filter, etc. Especially, the proposed method provides high detection rate and preserves the detail very well.
Target feature-enhanced processing of SAR image is meaningful to SAR ATR. One regularization method based on <i>l<sub>k</sub></i> norm used for target feature-enhanced of SAR image is discussed in this paper. This method exploits the useful sparse prior information which is well consistent to the statistically property of SAR image, makes up the additional constraint condition, turns the problem of target feature-enhanced processing of SAR image into the simple-formed optimization problem. A fast iterative algorithm is proposed to solve the optimization problem. The Simulation results and computational results of measured data prove its validity.