we propose a model-based interference cancellation procedure to overcome interference that is computationally inexpensive and provides a significant performance improvement. Specifically, we exploit this spectral diversity to realize a three-fold increase in the data rate by encoding independent data in the C, M, and Y print colorant channels and decoding the data from the complementary R, G, and B channels captured via a mobile phone camera. To mitigate the effect of cross-channel interference among the print colorant and capture color channels, we develop an algorithm for interference cancellation based on a physically-motivated mathematical model for the print and capture processes. To estimate the model parameters required for cross-channel interference cancellation, we propose two alternative methodologies: a pilot block approach that uses suitable selections of colors for the synchronization blocks and an expectation maximization approach that estimates the parameters from regions encoding the data itself. Experimental results show that the proposed framework successfully overcomes the impact of the color interference, providing a low bit error rate and a high decoding rate for each of the colorant channels when used with a corresponding error correction scheme.