Javidi B, Parchekani F, Zhang G
Appl Opt. 1996 Dec 10;35(35):6964-75. doi: 10.1364/AO.35.006964.
A minimum-mean-square-error filter is proposed to detect a noisy target in spatially nonoverlapping background noise. In this model, both the background noise that is spatially nonoverlapping with the target and the noise that is additive to the target and the input image are considered. The criterion used to design the filter is to minimize the mean-square-error between the filter output and a delta function located at the target position in the presence of the noise. Computer-simulation results for a number of noisy input images are presented, and the performance of the filter is determined. We also test the filter discrimination against undesired objects and tolerance to target distortions, such as rotation and scaling.
提出了一种最小均方误差滤波器，用于在空间上不重叠的背景噪声中检测有噪声的目标。在该模型中，既考虑了与目标在空间上不重叠的背景噪声，也考虑了加性于目标和输入图像的噪声。设计滤波器所使用的准则是在存在噪声的情况下，使滤波器输出与位于目标位置的狄拉克函数之间的均方误差最小化。给出了一些有噪声输入图像的计算机模拟结果，并确定了滤波器的性能。我们还测试了该滤波器对不期望物体的辨别能力以及对目标失真（如旋转和缩放）的容忍度。
