Affiliations: Department of Engineering Physics, Tsinghua
University, Beijing, 100084, China | Department of Nuclear Engineering, University of
Illinois at Urbana Champaign, IL, USA
Abstract: X-ray images are often of low contrast due to the subtle distinction
of attenuation coefficients and scatter effect, which makes it difficult to
distinguish signals from background. This paper proposes an image enhancement
algorithm using the multi-scale dyadic wavelet transform. The algorithm
includes two steps: 1) In order to enhance contrast, a non-linear mapping is
performed on wavelet coefficients at different scales. Inhibition factors are
then applied to reduce the impact of scatter; 2) In order to reduce the
negative impact of noise amplification from the first step, wavelet
coefficients are classified into two categories: irregular coefficients and
edge-related and regular coefficients, and then filtered with different schemes
for each category. Experimental results demonstrate that this algorithm
effectively enhance the contrast of x-ray images. Examination is also done on
CT reconstructions from multi-view projection data processed by the proposed
method and significant improvement of image quality is observed. Our results
are expected to offer great help to follow-up detection and recognition
tasks.
