Image-based rock typing is carried out to classify an image of the heterogeneous rock sample into different rock types where each rock type can be treated as a homogeneous porous medium. In this study, we propose an innovative method for rock typing of the heterogeneous rock sample via three steps. First, the target image, a segmented binary image with two phases of pore and solid, is consecutively inputted into two filters of a local homogeneity filter and an average filter to increase the contrast between different rock types and decrease the contrast within each single rock type. Second, Chan-Vese model is applied to classify the filtered image into different rock types. Third, a thresholding is used to remove the particles, which are treated as noisy particles, smaller than a given preset size. The main idea of the local homogeneity filtering introduced in this study is undertaken by counting the number of pixels that possess the same phases as the center pixel within a 3 × 3 pixels neighborhood. This process is carried out iteratively, which means the previously estimated pixel will be used in the estimation of its neighbor unprocessed pixels. We demonstrate the application of the proposed method in several heterogeneous images and present good performance.

进行基于图像的岩石分型以将非均质岩石样品的图像分类为不同的岩石类型，其中每种岩石类型都可以视为均质的多孔介质。在这项研究中，我们提出了一种创新的方法，可通过三个步骤对非均质岩石样品进行岩石分型。首先，将目标图像（具有孔隙和固体两相的分段二值图像）连续输入到局部同质性滤波器和平均滤波器的两个滤波器中，以增加不同岩石类型之间的对比度并降低每种单一岩石类型中的对比度。其次，使用Chan-Vese模型将滤波后的图像分类为不同的岩石类型。第三，阈值用于去除小于给定预设大小的被视为嘈杂粒子的粒子。这项研究中引入的局部均匀性滤波的主要思想是通过对3×3像素邻域内与中心像素具有相同相位的像素数进行计数。该过程是迭代执行的，这意味着先前估计的像素将用于估计其相邻未处理的像素。我们演示了在几种异构图像中提出的方法的应用，并表现出良好的性能。