Feature Enhancement in Low Quality Images with Application to Echocardiography

In this paper we propose a novel approach to feature enhancement to enhance the quality of noisy images. Our approach is based on a phase-based feature detection algorithm, followed by sparse surface interpolation and subsequent nonlinear post processing. We first exploit the intensity-invariant property of phase-based acoustic feature detection to select a set of relevant image features in the data. Then, an approximation to the low frequency components of the sparse set of selected features is obtained using a fast surface interpolation algorithm. Finally, a non-linear post-processing step is applied. Results of applying the method to echocardiographic sequences (2D+T) are presented. We show that our correction is consistent over time and does not introduce any artefacts. An evaluation protocol is proposed in the case of echocardiographic data and quantitative results are presented.