Noise-optimal capture for high dynamic range photography

Taking multiple exposures is a well-established approach both for capturing high dynamic range (HDR) scenes and for noise reduction. But what is the optimal set of photos to capture? The typical approach to HDR capture uses a set of photos with geometrically-spaced exposure times, at a fixed ISO setting (typically ISO 100 or 200). By contrast, we show that the capture sequence with optimal worst-case performance, in general, uses much higher and variable ISO settings, and spends longer capturing the dark parts of the scene. Based on a detailed model of noise, we show that optimal capture can be formulated as a mixed integer programming problem. Compared to typical HDR capture, our method lets us achieve higher worst-case SNR in the same capture time (for some cameras, up to 19 dB improvement in the darkest regions), or much faster capture for the same minimum acceptable level of SNR. Our experiments demonstrate this advantage for both real and synthetic scenes.Natural Sciences and Engineering Research Council of Canada (NSERC). Postdoctoral FellowshipNational Science Foundation (U.S.). Career Award (0447561)Quanta Computer (Firm)United States. National Geospatial-Intelligence Agency (NEGI-1582-04-0004)United States. Army Research Office. Multidisciplinary University Research Initiative (Grant Number N00014-06-1-0734)Microsoft CorporationGoogle (Firm)Adobe SystemsAlfred P. Sloan Foundation. FellowshipMicrosoft Research. New Faculty Fellowshi