In this paper we present a novel model of the primary visual cortex (V1) based on orientation, frequency and phase selective behavior of the V1 simple cells. We start from the first level mechanisms of visual perception: receptive profiles. The model interprets V1 as a fiber bundle over the 2-dimensional retinal plane by introducing orientation, frequency and phase as intrinsic variables. Each receptive profile on the fiber is mathematically interpreted as a rotated, frequency modulated and phase shifted Gabor function. We start from the Gabor function and show that it induces in a natural way the model geometry and the associated horizontal connectivity modeling the neural connectivity patterns in V1. We provide an image enhancement algorithm employing the model framework. The algorithm is capable of exploiting not only orientation but also frequency and phase information existing intrinsically in a 2-dimensional input image. We provide the experimental results corresponding to the enhancement algorithm.

翻译：在本文中,我们展示了一个基于V1简单单元格的方向、频率和阶段选择行为的初级视觉皮层(V1)的新模型。我们从第一级视觉感知机制:可接受性剖面。模型将V1解释为二维视网膜上的纤维捆绑,引入定向、频率和阶段为内在变量。纤维上的每个可接受性剖面在数学上被解释为一个旋转、频率调制和相向转换的加博功能。我们从加博函数开始,并显示它自然地诱发模型几何和相关的横向连通性模型以V1神经连通模式建模。我们利用模型框架提供了一种图像增强算法。算法不仅能够利用方向,而且能够利用二维输入图像中固有的频率和阶段信息。我们提供了与增强算法相对应的实验结果。