The colorful appearance of a physical painting is determined by the distribution of paint pigments across the canvas, which we
model as a per-pixel mixture of a small number of pigments with multispectral absorption and scattering coefficients. We present an
algorithm to efficiently recover this structure from an RGB image, yielding a plausible set of pigments and a low RGB reconstruction error.
We show that under certain circumstances we are able to recover pigments that are close to ground truth, while in all cases our results
are always plausible. Using our decomposition, we repose standard digital image editing operations as operations in pigment space
rather than RGB, with interestingly novel results. We demonstrate tonal adjustments, selection masking, cut-copy-paste, recoloring,
palette summarization, and edge enhancement.