Affiliations: ICT Research Center, Key Laboratory of Optoelectronic
Technology and System of the Education Ministry of China, Chongqing University,
Chongqing 400030, China | Key Laboratory of Optoelectronic Technology and System
of the Education Ministry of China, Chongqing University, Chongqing 400030,
China
Abstract: Multiresolution Analysis (MRA) plays an important role in image and
signal processing fields, and it can extract information at different scales.
Image fusion is a process of combining two or more images into an image, which
extracts features from source images and provides more information than one
image. The research presented in this article is aimed at the development of an
automated imaging enhancement system in digital radiography (DR) images, which
can clearly display all the defects in one image and don't bring blocking
effect. In terms of characteristic of the collected radiographic signals, in
the proposed scheme the subsection of signals is mapped to 0–255 gray scale to
form several gray images and then these images are fused to form a new enhanced
image. This article focuses on comparing the discriminating power of several
multiresolution images decomposing methods using contrast pyramid, wavelet, and
ridgelet respectively. The algorithms are extensively tested and the results
are compared with standard image enhancement algorithms. Tests indicate that
the fused images present a more detailed representation of the x-ray image.
Detection, recognition, and search tasks may therefore benefit from this.
