Vehicle Imaging ROI Processing for Low-Latency Driver Highlighting
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Solution Overview
Problem
Existing imaging systems for vehicles require significant additional processing time and computing resources to overlay information on camera images, leading to inefficiencies.
Innovation Solution
An imaging system for vehicles that processes image data by defining subsets of pixel values corresponding to regions of interest, applying specific image processing techniques such as color change, scaling, and high dynamic range (HDR) to these subsets, and merging them to generate an output image, reducing the need for post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If information is overlaid on the image after processing, then additional information is provided to the driver, but processing time and computing requirements increase
Solution Approach 1:
The patent applies preliminary action by identifying regions of interest and applying processing techniques (color changes, scaling, HDR) to these specific regions during the initial image processing stage, rather than performing overlay operations after the complete image is processed. This allows information highlighting to be built into the base image processing pipeline, eliminating the need for separate post-processing overlay steps and reducing total processing time
2Loss of information
If information is overlaid on the image after processing, then additional information is provided to the driver, but computing requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the image into regions of interest and non-regions of interest, then applying different processing techniques to each segment. By focusing computational resources only on the relevant regions (such as distance lines, objects, or icons) rather than processing the entire image uniformly, the system reduces overall computing requirements while still providing necessary information highlighting
Solution Approach 2:
The patent applies local quality by applying enhanced processing (color changes, scaling, HDR) only to specific regions of interest rather than the entire image. This localized approach ensures that computational power is concentrated where it is most needed for driver information, reducing total computing requirements compared to global image processing
3Reliability
If additional processing is performed for overlaying information, then driver alertness is enhanced, but processing efficiency decreases
Solution Approach 1:
The patent integrates region identification and processing enhancement into the preliminary image processing stage, so that when the image is displayed to the driver, the regions of interest are already highlighted and ready for immediate perception. This eliminates the need for additional post-processing overlay operations, maintaining both driver alertness through effective highlighting and processing efficiency by avoiding redundant computational steps
Data Source
AI summary
An imaging system includes an image sensor and an image signal processor (ISP). The image sensor generates image data including a set of pixel values. The ISP defines a first subset of pixel values from the set of pixel values. The first subset of pixel values corresponds to at least one region of interest. The ISP defines a second subset of pixel values that is complementary to the first subset of pixel values. The ISP generates a first sub-image based on the second subset of pixel values. The ISP processes the first subset of pixel values to generate a second sub-image. Processing the first subset of pixel values includes at least one of changing a color of one or more pixel values from the first subset of pixel values and scaling the first subset of pixel values. The ISP merges the first and second sub-images to generate an output image.