High Dimensional Data Decomposition for Anomaly Detection of Textured Images

This article likely presents a novel approach to anomaly detection in textured images using high-dimensional data decomposition techniques. The focus is on identifying unusual patterns or deviations within textured images, which could have applications in various fields like quality control, medical imaging, or surveillance. The use of 'ArXiv' as the source suggests this is a pre-print or research paper, indicating a contribution to the field of computer vision and potentially machine learning.