Color Temperature Tuning: Allowing Accurate Post-Capture White-Balance Editing

摘要

The in-cainera imaging pipeline consists of several routines that render the sensor's scene-referred raw-RGB image to the final display-referred standard RGB IsRGB) image. One of the crucial routines applied in the pipeline is white balance (WB). WB is performed to normalize the color cast caused by the scene's illumination, which is often described using correlated color temperature. WB is applied early in the in-camera pipeline and is followed by a number of nonlinear color manipulations. Because of these nonlinear steps, it is challenging to modify an image 's WB with a different color temperature in the sRGB image. As a result, if an sRGB image is processed with the wrong color temperature, the image will have a strong color cast that cannot be easily collected. To address this problem, we propose an imaging framework that renders a small number of "tiny versions" of the original image (e.g.. 0.1% of the full-size image), each with different WB color temperatures. Rendering these liny images requires minimal overhead from the camera pipeline. These tiny images are sufficient to allow color mapping functions to be computed that can map the full-sized sRGB image to appear as if it was rendered with any of the tiny images' color temperature. Moreover, by blending the color mapping functions, we can map Ihe output sRGB image to appear as if it was rendered through the camera pipeline with any color temperature. These mapping functions can be stored as a JPEG comment with less than 6 KB overhead. We demonstrate that this capture framework can significantly outperform existing solutions targeting post-capture WB editing.