Image Exposure Control via Weighted Channel Intensity
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Solution Overview
Problem
Multi-channel images, such as RGB images, can become overexposed due to uneven lighting conditions, leading to clipped pixels and reduced detail, which impede image processing operations like edge detection and object detection.
Innovation Solution
An image capture device adjusts exposure parameters using a weighted average of pixel intensities, with weights assigned based on luminosity functions or outlier channels to prevent overexposure, ensuring more accurate representation of average pixel intensity and reducing the likelihood of clipped pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If automatic exposure is adjusted based on average pixel intensity of all channels, then the exposure setting is simplified, but overexposure occurs in channels with disproportionately high intensity due to lighting conditions
Solution Approach 1:
The patent applies local quality by treating different color channels differently in the exposure calculation. Instead of uniformly averaging all channel intensities, it identifies the channel with disproportionately high intensity (outlier channel) and excludes it from the average calculation. This allows each channel to be evaluated according to its specific lighting characteristics, preventing overexposure in affected channels while maintaining overall exposure balance.
2Illumination intensity
If exposure parameters are set to capture bright scenes, then overall image brightness is improved, but detailed information is lost in overexposed regions due to clipped pixels
Solution Approach 1:
The patent implements feedback by using the detected outlier channel information to adjust exposure parameters for subsequent images. The system continuously monitors channel intensities, identifies when lighting conditions cause disproportionate intensity in one channel, and automatically modifies exposure settings to compensate. This closed-loop approach prevents overexposure and preserves detail information while maintaining appropriate image brightness.
Data Source
AI summary
An example method includes capturing, by an image capture device, a first image having a plurality of pixels. Each pixel includes a plurality of channels, and the first image is captured in accordance with first exposure parameters. The method includes determining, by a controller of the image capture device, average pixel intensities for each of the plurality of channels. The method includes determining, by the controller, a weighted average of pixel intensities using the average pixel intensities. The method includes setting, by the controller, a gain that is proportional to a ratio of a desired average pixel intensity relative to the weighted average of pixel intensities. The method includes setting, by the controller, second exposure parameters for a second image based on the gain. The method includes capturing, by the image capture device, the second image in accordance with the second exposure parameters.