Vehicle Vision Enhancement via HDR Tone Mapping and Contrast
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Solution Overview
Problem
Existing driver vision enhancement systems for vehicles under degraded visual conditions, such as fog and haze, face challenges in image quality due to attenuation and airlight effects, and thermal imaging systems are expensive and difficult for drivers to interpret quickly.
Innovation Solution
An enhanced imaging system utilizing a visible light camera and graphics processor to capture and process High-Dynamic-Range (HDR) images, tone map, and detect boundaries to generate an optimized signal that increases contrast between object and exterior tonal values, improving image clarity and readability on a display device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If thermal imaging cameras are used to enhance driver vision under degraded visual conditions, then visibility enhancement is achieved, but system cost increases and image interpretability decreases
Solution Approach 1:
The patent uses visible light cameras to capture images and creates a processed version (copy) of the visual scene through HDR tone mapping and contrast enhancement. This copy provides thermal-like visibility enhancement through computational methods rather than physical thermal sensing, avoiding the high cost of thermal imaging hardware while achieving similar visibility improvement under degraded conditions.
Solution Approach 2:
The patent replaces the mechanical/physical thermal imaging system with an optical system (visible light camera) combined with digital signal processing. Instead of using thermal radiation detection hardware, the system uses computational image processing (HDR tone mapping, boundary detection, contrast transformation) to achieve enhanced visibility, substituting a complex physical sensing system with a simpler optical capture and digital processing approach.
2Reliability
If thermal imaging cameras are used to enhance driver vision under degraded visual conditions, then visibility enhancement is achieved, but driver interpretation speed decreases
Solution Approach 1:
The patent applies contrast transformation and tone mapping that enhances edge boundaries and object contours through visual cues familiar to drivers. By detecting boundaries and transforming contrast to emphasize edges and shapes rather than temperature gradients, the system presents information in a visually intuitive format that drivers can interpret quickly using their existing visual processing skills.
Solution Approach 2:
The patent transforms the tonal parameters of the captured image through HDR tone mapping and contrast enhancement. By adjusting luminance and contrast parameters to emphasize boundaries and reduce haze effects, the system modifies the visual parameters in a way that maintains familiar visual characteristics while improving visibility, allowing drivers to interpret the enhanced image without needing to learn new thermal interpretation patterns.
3Device complexity
If visible light cameras are used to capture outdoor scenes, then system cost decreases, but image quality degrades under fog and haze conditions
Solution Approach 1:
The patent performs preliminary HDR tone mapping and contrast enhancement processing on the captured images to compensate for atmospheric degradation before display. By pre-processing the images with boundary detection and contrast transformation algorithms, the system anticipates and corrects for the quality loss that would otherwise occur under fog and haze conditions, maintaining acceptable image quality with standard visible light cameras.
Solution Approach 2:
The patent introduces digital signal processing algorithms as an intermediary between the visible light camera and the display device. This intermediary layer performs HDR tone mapping, boundary detection, and contrast enhancement to compensate for the image quality degradation caused by atmospheric conditions, allowing the use of inexpensive visible light cameras while maintaining effective image quality through computational correction.
Data Source
AI summary
An enhanced imaging system for a motor vehicle includes a vision processing module that generates a data signal, in response to the camera capturing at least one of the video and the image. A graphics processor is configured to tone map the video or image to generate an RGB histogram including an overall tonal range. The processor is further configured to compare the overall tonal range to a tonal threshold. The processor detects one or more objects having a boundary that separates an interior region having an object tonal value from an exterior region having an exterior tonal value. The processor generates an optimized signal for increasing a difference between the object tonal value and the exterior tonal value, in response to the overall tonal range being above the tonal threshold. The system can further include a display device for displaying an optimized video or image.