Figure 2:

Rank-Sparse Kernel Regression (RSKR) is a denoising algorithm designed for multi-energy CT data. (1) Example weighted singular value decomposition of dual-energy data which yields a high-fidelity average image and a lower fidelity difference image. (2–3) Denoising is performed by applying joint bilateral filtration, an edge preserving smoothing operation which matches edges between the average and difference images. Step 2 is alternated with fidelity updates (3), to prevent loss of image details, and further iterated as needed. (4) Denoised results following inversion of the singular value decomposition.