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具有高空间分辨率的脑内源性信号光学成像术是研究大脑皮层功能构筑的有力工具。针对非常微弱的内源性光学信号的提取,本文首先讨论了其噪声来源和基于生理结构原因的信号特征;然后根据由标准化处理得到的功能图像的二阶统计量分析结果,提出了自适应滤波窗口设计:使用非线性中值空域滤波,对含有不同特征的图像区域,分别采取不同的滤波窗口进行处理。图像处理结果表明,该算法去除噪声的效果优良,并能够保留皮层功能柱结构的细节特征。
Endogenous signal optical imaging with high spatial resolution is a powerful tool for studying the functional construction of the cerebral cortex. In order to extract very weak endogenous optical signals, this paper first discusses the sources of noise and the signal features based on the physiological structure. Then, based on the results of the second-order statistics analysis of the functional images obtained by normalization, adaptive filtering Window Design: Using non-linear median spatial filtering, different image filtering windows are used to deal with image regions with different features. The results of image processing show that the proposed algorithm can remove noise effectively and retain the detail features of cortical column structure.