A simplified HDR image processing pipeline for digital photography

High Dynamic Range (HDR) imaging has revolutionized the digital imaging. It allows capture, storage, manipulation, and display of full dynamic range of the captured scene. As a result, it has spawned whole new possibilities for digital photography, from photorealistic to hyper-real. With all these advantages, the technique is expected to replace the conventional 8-bit Low Dynamic Range (LDR) imaging in the future. However, HDR results in an even more complex imaging pipeline including new techniques for capturing, encoding, and displaying images. The goal of this thesis is to bridge the gap between conventional imaging pipeline to the HDR’s in as simple a way as possible. We make three contributions. First we show that a simple extension of gamma encoding suffices as a representation to store HDR images. Second, gamma as a control for image contrast can be ‘optimally’ tuned on a per image basis. Lastly, we show a general tone curve, with detail preservation, suffices to tone map an image (there is only a limited need for the expensive spatially varying tone mappers). All three of our contributions are evaluated psychophysically. Together they support our general thesis that an HDR workflow, similar to that already used in photography, might be used. This said, we believe the adoption of HDR into photography is, perhaps, less difficult than it is sometimes posed to be.