The human visual system is capable of identifying and processing visual features with high dynamic range. For example, real-world scenes with contrast ratios of 1,000,000:1 or greater can be accurately processed by the human visual cortex. However, most image acquisition devices are only capable of reproducing or capturing low dynamic range, resulting in a loss of image accuracy. The problem is ever more significant in video imaging.
There are examples of creating High Dynamic Range images by post processing images from multiple sensors, each subject to different exposures. The resulting “blended” image is intended to capture a broader dynamic range than would be possible from a single sensor without a post-processing operation.
Conventional approaches to capturing High Dynamic Range images include using sensors to acquire image frames of varying exposures and then processing those frames after acquisition (post-processing). Such approaches present significant challenges when filming video. If the subject, or camera, is moving then no pair of images will include exactly the same scene. In such cases, after the initial image capture, a post-processing step is required before a High Dynamic Range video can be produced.