LiDAR Camera Metering for Exposure and Depth-Aware Image Processing
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Solution Overview
Problem
Existing camera systems rely primarily on light metering for exposure adjustment, which may not adequately address variations in distance, material properties, and scene complexity, leading to suboptimal image quality.
Innovation Solution
Incorporating a LiDAR sensor to measure depth, position, reflectivity, and other properties to dynamically adjust exposure settings and post-processing techniques, such as HDR imaging and bokeh effects, based on these measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light metering sensor is used for exposure adjustment, then exposure settings can be determined, but image quality is suboptimal in complex scenes with varying distances and material properties
Solution Approach 1:
The patent segments the measurement function by introducing a LiDAR sensor that independently measures distance and material properties separate from the light metering sensor. This segmentation allows the system to obtain precise light measurements for exposure while simultaneously capturing depth and reflectivity data, resolving the contradiction between measurement precision and image quality reliability in complex scenes
Solution Approach 2:
The patent merges multiple measurement capabilities (light metering, depth sensing, reflectivity measurement) into a unified imaging system. By combining data from the light metering sensor and LiDAR sensor, the system achieves both accurate exposure measurement and reliable image quality across varying distances and material properties
2Adaptability or versatility
If traditional light-based metering is used, then exposure can be adjusted, but variations in distance and material properties cannot be adequately addressed
Solution Approach 1:
The patent implements multi-functionality by equipping the imaging system with both a light metering sensor and a LiDAR sensor. This universal measurement system can simultaneously perform exposure measurement, distance detection, and material property assessment, allowing the system to adapt to various shooting scenarios while accurately detecting and measuring multiple parameters
3Reliability
If LiDAR sensor is added to measure depth and material properties, then image quality improves, but device complexity increases
Solution Approach 1:
The patent uses the LiDAR sensor as an intermediary that provides depth and material property information to inform exposure decisions. This intermediary measurement system enables improved image quality by supplying additional contextual data without requiring a complete redesign of the core imaging architecture, thus managing device complexity while enhancing reliability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves image quality by optimizing exposure settings for varying distances and material properties, enhancing detail differentiation and realism, especially in complex lighting conditions.
Implementation Method 1
a LiDAR sensor to measure depth, position, reflectivity, and other properties
Data Source
AI summary
Disclosed is Light Detection and Ranging (“LiDAR”)-based camera metering, exposure adjustment, and image postprocessing. The LiDAR-based exposure adjustment may include emitting a laser from an imaging device, obtaining one or more measurements based on the laser reflecting off one or more objects in a scene and returning to the imaging device, adjusting exposure settings of the imaging device based on the one or more measurements, and capturing an image of the scene using the exposure settings. The LiDAR-based image postprocessing may include receiving an image of a scene and measurements or outputs from a LiDAR scan of the scene, and performing different adjustments to color values, contrast, brightness, saturation, levels, and other visual characteristics of different sets of pixels in the image based on different distance, material property, and/or other measurements obtained by the LiDAR for objects represented by the different sets of pixels.