Textile image enhancement aims to extract textural features of textiles which facilitates manual testing and machine vision inspection of textile.In this paper

a method for textile image enhancement is proposed in the framework of non-local means (NLM) filtering.Due to the periodic nature of textiles

there exists a lot of redundant information in textile images which can be used to enhance the texture information.However

the complex structures of textile images as well as the presence of image noise tend to distort similarity measures of the NLM algorithm.To solve this problem

principal component analysis (PCA) is used to decompose textile images into information components and noise components

and remove the correlation between the components for improving the accuracy of the similarity measure between textile textures.The experimental results demonstrate that the proposed method has substantially improved the performance of texture enhancement relative to the existing texture enhancement methods.