Vehicle Camera Image Contrast Enhancement via Exposure Stacking
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Solution Overview
Problem
Vehicle imaging systems struggle to detect objects in poor visibility conditions such as dense fog, as existing image processing algorithms fail to enhance image contrast effectively, leading to difficulty in identifying objects for both the driver and the system.
Innovation Solution
The system employs brightness transfer function filtering and exposure stacking to amplify image contrast, tracking contrast thresholds on a frame-by-frame basis, generating pseudo-high dynamic range images by tone mapping and blending current and historical image components, which enhances object detectability in foggy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing image processing algorithms are used, then the system is simple to operate, but object detection fails in poor visibility conditions such as dense fog
Solution Approach 1:
The system performs preliminary actions by capturing multiple exposure images at different brightness levels before object detection is needed. These pre-captured images with varying exposures are then combined to create an enhanced image with improved contrast and visibility, allowing reliable object detection in poor visibility conditions without requiring complex real-time processing during critical moments
Solution Approach 2:
The system merges multiple image components captured at different exposure levels into a single enhanced image. By combining the bright areas from overexposed images with the dark area details from underexposed images, the system creates a composite image that preserves both highlight and shadow information, significantly improving object detectability in foggy conditions
2Measurement precision
If brightness transfer function filtering and exposure stacking are applied, then image contrast is amplified improving object visibility, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary image capture and stacking operations before critical detection is needed. Multiple exposure images are captured and combined in advance, creating a pre-processed enhanced image that requires minimal additional processing during actual object detection, thereby reducing real-time processing time while maintaining high contrast precision
Solution Approach 2:
The system dynamically adjusts the image processing pipeline based on visibility conditions. In poor visibility conditions, the full brightness transfer function filtering and exposure stacking process is applied to maximize contrast. In good visibility conditions, processing is reduced or skipped, optimizing the balance between processing time and image contrast enhancement
Data Source
AI summary
A method of image enhancement for a vehicle vision system includes providing a camera at the vehicle and providing a processor operable to process image data. Multiple frames of image data are captured with the camera, and contrast is enhanced in image data by tone mapping. As the vehicle moves, contrast thresholds are tracked within the captured frames of image data with respect to image flow caused by the vehicle's movement. Image data of a first frame of captured image data may be passed through two individual image transfer functions to generate a first transferred frame of image data. The first transferred frame may be blended with a second frame of image data. Presence of an object is detected in the field of view of the camera, and an output is generated responsive to detection of the object present in the field of view of the camera.