基于相干特征的岩石薄片序列图像边缘提取及颗粒分割

针对岩石颗粒边缘模糊、结构复杂的特点，为了更有效地识别颗粒边缘，在基于特征值的C3相干算法的基础上，融合多尺度和多角度的特征表达，提出了一种改进的C3相干算法。该算法综合考虑岩石薄片图像角度域光学特征、空间尺度信息和各向异性信息，能更有效地表征颗粒边缘特征，表现出对复杂矿物结构的适应能力。在采集的岩石薄片正交偏光图像上验证提出的算法，实验结果表明，与原生C3相干算法相比，改进后的C3相干算法在全局图像上的方差和灰度差分乘积分别提升了68.41%和22.91%，信息熵下降了21.61%。

Edge Extraction and Particle Segmentation Based on Coherent Features of Rock Slice Sequence Images

Aiming at the characteristics of fuzzy edges and complex structures of rock particles, an improved C3 coherence algorithm is proposed to identify the edges of particles more effectively. The improved C3 coherence algorithm is based on eigenvalues, in which the multi-scale and multi-angle feature expressions are infused for improvement. It comprehensively considers the angle domain optical characteristics, spatial scale information, and anisotropy information of rock slice images so that the grain edges are characterized more effectively, which have strong noise resistance and adaptability to complex mineral structures. The proposed algorithm has been verified on the acquired orthogonal polarized images of rock slices. The experimental results show that compared with the native C3 coherence algorithm, the improved C3 coherent algorithm increases the variance and gray-scale difference product of the global image by 68.41% and 22.91%, and decreases the information entropy by 21.61%.