Depth-Based Exposure Computation for High Dynamic Range Imaging
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Solution Overview
Problem
Current digital camera exposure algorithms often yield unacceptable results due to the influence of background light levels on foreground exposure, leading to suboptimal photographs with unbalanced illumination.
Innovation Solution
Implementing a 3D camera system that segments a scene based on depth, allowing for accurate determination of the foreground subject of interest and adjusting exposure parameters like aperture, shutter speed, and illumination to match discrete compositional zones, thereby achieving correct illumination of both foreground and background.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single exposure level is used for the entire scene, then the camera operation is simple and fast, but the foreground and background cannot both be correctly exposed when they have different light levels
Solution Approach 1:
The scene is segmented into multiple depth-based zones using a depth map, where each zone corresponds to a different exposure level. This allows the camera to apply different exposure parameters to different spatial regions, enabling correct exposure of both foreground and background subjects simultaneously.
Solution Approach 2:
Different exposure parameters (shutter speed, aperture, ISO) are applied locally to different depth zones rather than uniformly across the entire scene. This ensures that each region receives the optimal exposure settings appropriate for its specific lighting conditions and distance from the camera.
2Reliability
If multiple images at different exposures are captured and combined, then high dynamic range and natural illumination are achieved, but the processing time and computational complexity increase
Solution Approach 1:
A depth map of the scene is generated in advance before exposure computation, allowing the system to pre-determine the optimal exposure parameters for each depth zone. This preliminary depth-based segmentation enables efficient exposure calculation without requiring iterative processing of multiple full images.
Solution Approach 2:
Instead of capturing and processing multiple full-resolution images at different exposures, the system uses a depth map (a simplified representation) to guide exposure parameter selection. This copying approach allows the system to work with lightweight depth information rather than heavy image data, reducing processing time.
3Ease of manufacture
If traditional zone-based metering is used to determine exposure, then the exposure calculation is simple, but background light levels incorrectly influence foreground exposure
Solution Approach 1:
The exposure calculation transitions from two-dimensional zone-based metering in the image plane to three-dimensional depth-based zoning using a depth map. By incorporating the depth dimension, the system can distinguish between foreground and background regions and calculate exposure parameters that are independent of background lighting conditions.
Data Source
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AI summary
A method and electronic information handling system provide recording a first image of a scene at a first exposure level using a three-dimensional (3D) camera, correlating distances from the 3D camera and exposure levels over a plurality of image elements of the first image, selecting an exposure parameter value for at least one of the plurality of image elements having a z-distance value falling within a range of z-distance values, recording a second image of the scene according to the exposure parameter value, and constructing a composite image based on at least a portion of the second image for the at least one of the plurality of image elements.