In this work, we used nonlocal priors in a Bayesian approach for X-ray scatter correction. The control parameters of our algorithms such as the patch sizes and search areas were set in such a way that significant improvement in correction results can be achieved. This, however, led to drastic increases in computation time. To solve this problem, we developed a novel multi-grid technique based on some observations on the matching process involved in the nonlocal priors. Experimental results have demonstrated that this technique is effective, accelerating the computation time significantly while maintaining the quality of correction results. In addition to scatter correction, it can also be used for other image processing applications where fast high-dimensional nonlocal filtering is needed.
In X-ray imaging, scatter can produce noise, artifacts, and decreased contrast. In practice, hardware such as anti-scatter grids are often used to reduce scatter. However, the remaining scatter can still be significant and additional software-based correction are desirable. Furthermore, good software solutions can potentially reduce the amount of needed anti-scatter hardware, thereby reducing cost. In this work, we developed a software correction algorithm by adapting a class of non-local image restoration techniques to scatter reduction. In this algorithm, scatter correction is formulated as a Bayesian MAP (maximum a posteriori) problem with a non-local prior, which leads to better textural detail preservation in scatter reduction. The efficacy of our algorithm is demonstrated through experimental and simulation results.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.