Fast, high dynamic range light field processing for pattern recognition

We present a light field processing method to quickly produce an image for pattern recognition. Unlike processing for aesthetic purposes, our objective is not to produce the best-looking image, but to produce a recognizable image as fast as possible. By leveraging the recognition algorithm's dynamic range and robustness to optical defocus, we develop carefully-chosen tradeoffs to ensure recognition at a much lower level of computational complexity. Capitalizing on the algorithm's dynamic range yields large speedups by minimizing the number of light field views used in refocusing. Robustness to optical defocus allows us to quantize the refocus parameter and minimize the number of interpolations. The resulting joint optimization is performed via dynamic programming to choose the set of views which, when combined, produce a recognizable refocused image in the least possible computing time. We demonstrate the improved recognition dynamic range of barcode scanning using a Lytro camera, and dramatic reductions in computational complexity on a low-power embedded processor.