M滤波的自适应背景抑制算法

New Adaptive Background Suppression Algorithm Via M-filter

提出了一种M滤波的自适应背景抑制算法。该算法将目标和观测噪声作为图像背景的混合干扰,依据M估计原理自适应的估计真实背景。算法具有较好的稳健性能,能够自适应的低抗高强度的干扰。仿真和实验表明,与均值滤波(MF)、中值滤波(ModF)以及Wiener滤波(WF)相比,该算法能够更有效地从混合噪声环境下估计背景,增强目标信噪比(SNR)。

Background suppression is a key technique to the automatic detection and tracking small and dim objects. And a daptive background estimation is an efficient way to realize this technique. To the problem, an M-filter adaptive background suppression algorithm is presented. In the algorithm, the image background is considered as the mixed interference by the target and observing noises,and the tree image background is estimated adaptively via M-estimation. This algorithm is robustness and can resist high mixed interference. Simulations and experiments show that the algorithm is more efficient to estimate the background and improve signal to noise ratio（SNR） im mixed noises compared with the mean filter method, the median filter method and the Wiener filter method.