关键词: 噪声抑制, 模板迭代, 非线性模型, 推广卡尔曼滤波

Abstract: There are three major problems in respect of image de-noising：the first is the contradiction between noise depression and detail preservation；the second is the contradiction between the real time request and the algorithm complexity；the third one is the contradiction between the idealized statistical model and the variety of the real noise. As different types of filter templates are adaptable to different noise models and different sizes of filter templates retain varying degrees of detail, the state equation and observation equation are established for different types and sizes of filter templates, and a nonlinear model is approximated a linear model by the use of Extended Kalman Filter（EKF） theory. Image is de-noised depending on observed value of different templates. The simulated result shows that Kalman filter based on template iteration has advantages such as less calculation, more rapid speed and higher quality, especially adaptation to mixed noise compared with other filter algorithms.

Key words: de-noising, template iteration, nonlinear model, Extended Kalman Filter（EKF）