title: Study of automatic enhancement for chest radiograph.
abstract: Because of the large difference of the densities in the lung and other structures, the chest x-ray image behaves as a wide-range intensity distribution, which brings on a bit of difficulty to investigate the focus. In the paper, according to the intensity properties of the chest radiograph, the chest radiographic image is divided into three subregions, and a piecewise linear transformation model is established. An approach of automatic enhancement is presented, based on the gray-level normalization. The average enhanced ratios of three subregions of the normal and severe acute respiratory syndrome image are increased by 10.70% and 25.55%, respectively. The technique is proved to be effective through the evaluation of the improved images.
authors.affiliation: The Key Laboratory of the State Education Ministry on Instrumentation Science and Dynamic Measurement, North University of China, Taiyuan, 030051, People's Republic of China.
authors.forename: Chen
authors.initials: C
authors.lastname: Shuyue
authors.forename: Hou
authors.initials: H
authors.lastname: Honghua
authors.forename: Zeng
authors.initials: Z
authors.lastname: Yanjun
authors.forename: Xu
authors.initials: X
authors.lastname: Xiaomin
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted; D011856:Radiographic Image Enhancement / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*