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Coupled Wilson-Cowan Oscillator Model with Double-Node for Image Enhancement

机译:具有双节点的Wilson-Cowan振荡器模型耦合用于图像增强

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In this work, a model mimicking cerebral rhythms based on the coupled Wilson-Cowan oscillator with double nodes is proposed to achieve image enhancement. The inputs of the model are images to be enhanced and the outputs are node responses of excited subpopulation. To explain the mechanisms of the method, parameters are selected to meet conditions of limit cycles. Thus, in those conditions, the model produce oscillation by means of nonlinear dynamic analysis. In our experiments, image patches with continuous gray values are employed as stimulus and the response curves are similar to classical Gamma correction curves. Is it implicit that the Gamma correction can be explained by some cerebral rhythms? After some comparisons with other methods, the model proposed in the work shows better results.
机译:在这项工作中,提出了一种基于耦合的Wilson-Cowan振荡器与双节点的模型模拟脑节奏,以实现图像增强。模型的输入是要增强的图像,并且输出是激发亚群的节点响应。为了解释该方法的机制,选择参数以满足限制循环条件。因此,在这些条件下,模型通过非线性动态分析产生振荡。在我们的实验中,使用连续灰度值的图像贴片作为刺激,并且响应曲线类似于古典伽马校正曲线。是否隐含伽玛校正可以通过一些脑节奏解释?在与其他方法进行一些比较之后,工作中提出的模型显示出更好的结果。

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