Studying the Statistics of Natural X-ray Pictures

作者：Gupta Praful^*; Glover Jack L; Paulter Nicholas G Jr; Bovik Alan C

来源：Journal of Testing and Evaluation, 2018, 46(4): 1478-1488.

DOI：10.1520/JTE20170345

• natural scene statistic
• X-ray images
• modality classification
• National Institute of Standards and Technology

In this article, we have studied and analyzed the statistics of both pristine and distorted bandpass X-ray images. In the past, we have shown that the statistics of natural, bandpass-filtered visible light (VL) pictures, commonly expressed by natural scene statistic (NSS) models, can be used to create remarkably powerful, perceptually relevant predictors of perceptual picture quality. We find that similar models can be developed that apply quite well to X-ray image data. We have also studied the potential of applying these statistical X-ray NSS models to the design of algorithms for automatic image quality prediction of X-ray images, such as might occur in security, medicine, and material inspection applications. As a demonstration of the discrimination power of these models, we devised an application of NSS models to an image modality classification task, whereby VL, X-ray, infrared, and millimeter-wave images can be effectively and automatically distinguished. Our study is conducted on a dataset of X-ray images made available by the National Institute of Standards and Technology.

• 出版日期2018-7