基于四元数Gabor滤波的彩色纹理特征提取

现有的彩色图像纹理特征提取方法是将彩色图像转换为灰度图像或者对彩色图像进行分通道处理，这样的处理方法会丢失原图像的颜色信息和各通道间的相关性，导致特征图像的纹理特征和原图像的纹理特征差异较大。基于上述问题，提出了一种四元数Gabor彩色纹理特征提取方法。首先，根据Gabor滤波和四元数欧拉公式，推导出四元数Gabor滤波，并将彩色图像用四元数矩阵表达；其次提出四元数Gabor滤波卷积算法处理彩色图像，得到多尺度多方向的彩色纹理特征图像；最后对得到的彩色纹理特征图像进行Tamura统计特征的提取。实验结果表明，该方法可以很大程度地保留原图像的粗糙度、对比度和方向度等纹理特征，同时可以提取到原图像的颜色信息。在转化为灰度图像后，该方法在保留粗糙度、对比度和方向度等纹理特征方面优于传统Gabor方法和LBP方法。

Color texture features extraction based on quaternion Gabor

Current color texture feature extraction methods transform color images into gray images or process color image by channel separation, which can lead to color information loss of the original image or correlation loss between channels, so that the texture feature of the feature image differs greatly from that of the original image. To solve the above mentioned problems, we propose a quaternion Gabor method to extract color texture features. Firstly, quaternion Gabor filter is deduced according to traditional Gabor filter and quaternion Euler’s formula, and the color image is described by Quaternion field. Secondly, we propose a quaternion Gabor convolution algorithm to process the color image, and obtain a multi scale, multi direction color texture image. Finally, Tamura statistical feature is extracted from the color texture image. Experimental results show that the proposed method can maintain text features of the original image such as coarseness, contrast and directionality to a great extent and meanwhile obtain color information, which outperforms the traditional Gabor feature image and LBP method.