Nonlinear multi-scale contrast enhancement for chest radiograph

Recently, extensive research and application on contrast enhancement of radiographs based on multi-scale decomposition of the images have validated its higher performance than regular techniques. However, to some extent, conventional multi-scale methods suffered from the introduction of visible artifacts. In this work, we present an algorithm for nonlinear chest radiograph contrast enhancement algorithm within the multi-scale decomposition architecture in spatial domain. In particular, one kind of nonlinear enhancement function is designed by exploiting local contrast information. The main contribution of this model is the local adaptive enhancement ability, which can avoid visible artifacts, while keeping the same detail enhancement ability. In the meantime, no excessive noise is amplified, comparing to conventional methods. Finally, an evaluation using a chest image is provided to demonstrate the effectiveness of the proposed algorithm.