X-ray image enhancement based on the dyadic wavelet transform

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.