Vehicle Image Processing Pipeline with Navigation-Only Steps
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Solution Overview
Problem
Autonomous vehicles face inefficiencies in image processing due to unnecessary steps in the image and signal processing pipeline, which delays the readiness of images for navigation tasks.
Innovation Solution
A streamlined image processing pipeline is implemented, omitting steps not essential for vehicle navigation, utilizing a camera and image signal processing pipeline that generates and processes images efficiently for navigation purposes, with the ability to adapt processing based on the vehicle's state and intended use of the images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a complete image and signal processing pipeline is used, then image processing quality is improved, but processing time increases
Solution Approach 1:
The patent extracts and removes unnecessary processing steps from the complete image processing pipeline. Specifically, it identifies and omits steps such as tone mapping, color space conversion, and other post-processing operations that are not essential for autonomous vehicle navigation, retaining only the critical steps needed for navigation tasks.
Solution Approach 2:
The patent segments the image processing pipeline into essential and non-essential components. It divides the processing steps into those required for navigation (e.g., basic image capture, noise reduction, edge detection) and those that can be omitted (e.g., display-optimized processing), allowing selective execution of only the necessary segments.
2Measurement precision
If a complete image and signal processing pipeline is used, then image processing quality is improved, but computational resources increase
Solution Approach 1:
The patent extracts and eliminates computationally intensive processing steps that do not contribute to navigation functionality. By removing operations such as high-quality color rendering, advanced tone mapping, and other resource-heavy processing tasks, it significantly reduces computational resource consumption while preserving the essential image processing quality needed for navigation.
Solution Approach 2:
The patent applies partial action by executing only the necessary portion of the image processing pipeline required for navigation tasks. Instead of performing the complete processing sequence, it executes only the minimal set of operations needed to produce navigation-ready images, avoiding excessive computational expenditure on non-essential processing steps.
3Speed
If image processing steps are omitted, then processing speed is improved, but image quality for non-navigation purposes deteriorates
Solution Approach 1:
The patent applies local quality by optimizing image processing specifically for the navigation function rather than applying uniform high-quality processing to all aspects. It tailors the processing pipeline to provide sufficient quality for navigation tasks (edge detection, object recognition, depth perception) while omitting processing steps that would only improve quality for human viewing or other non-navigation purposes.
Solution Approach 2:
The patent implements a dynamic processing pipeline that adapts the level and type of processing based on the specific navigation context and requirements. The system can dynamically adjust which processing steps are executed based on real-time needs, ensuring processing speed is optimized while maintaining adequate image quality for the current navigation task.
Data Source
AI summary
Provided are methods for managing efficiency of image processing, which can include obtaining, using at least one SoC, raw data associated with a raw image from at least one camera; generating an updated image based on the raw image from the at least one camera, wherein the updated image represents photons received by the at least one camera; providing the updated image to an image and signal processing pipeline; processing the updated image using the image and signal processing pipeline; and operating a vehicle based at least in part on information obtained from an analysis of the processed image.