Camera Raw Data Preprocessing for Bandwidth Reduction
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Solution Overview
Problem
The increasing demand for high image resolution and temporal sampling in cameras, particularly in driver assistance systems and robotics, leads to a significant increase in data traffic and bandwidth requirements, which existing technologies struggle to manage efficiently, resulting in high system and energy costs.
Innovation Solution
A method and device for preprocessing camera raw data that reduces the resolution of camera data by adapting the preprocessing algorithm based on dynamic movements, object detection, and external signals, allowing for application-specific data reduction and optimization of memory and transmission bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera resolution and temporal sampling are increased to meet growing requirements in driver assistance systems and robotics, then image quality and detection capability are improved, but data traffic and bandwidth requirements increase significantly
Solution Approach 1:
The patent segments the camera system into multiple independent processing channels (e.g., first camera channel and second camera channel) that can operate with different resolutions and sampling rates. This allows critical areas or applications to receive high-resolution data while less critical areas use lower resolution, thereby maintaining measurement precision where needed while reducing overall data traffic.
Solution Approach 2:
The patent applies local quality by allowing different image areas to be processed at different resolutions based on their importance. High-resolution processing is applied selectively to regions containing relevant objects or events, while other regions are processed at lower resolution. This maintains the necessary measurement precision for critical areas while significantly reducing the total data volume.
2Reliability
If multiple cameras are deployed to enhance coverage and detection capabilities, then system reliability and detection accuracy are improved, but data volume and processing load increase
Solution Approach 1:
The patent divides the camera system into multiple independent channels, each capable of autonomous preprocessing. This segmentation allows each camera's data to be processed separately and efficiently, maintaining high detection accuracy through multi-camera coverage while managing data volume through localized preprocessing before aggregation.
Solution Approach 2:
The patent implements preliminary action by performing preprocessing operations (such as resolution reduction, filtering, or feature extraction) on camera data before the main processing stage. This early processing reduces the data volume that needs to be handled by subsequent systems while preserving the essential information needed for reliable detection and accuracy.
3Measurement precision
If high resolution and high sampling rates are maintained throughout the processing chain, then image quality is preserved, but memory bandwidth and transmission bandwidth requirements become prohibitive
Solution Approach 1:
The patent applies local quality by processing different regions of the image at different resolutions according to their importance. Critical regions maintaining high image quality are processed at full resolution, while non-critical regions are processed at lower resolution. This selective approach preserves necessary image quality while dramatically reducing memory bandwidth and transmission bandwidth requirements.
Solution Approach 2:
The patent implements partial action by applying high-resolution processing only to the extent necessary for the specific application requirements. Rather than processing the entire image at maximum resolution, only essential portions are processed at high quality, reducing bandwidth consumption while maintaining sufficient image quality for the intended purpose.
Data Source
AI summary
A method for preprocessing camera raw data of an image sensor of a camera. The method includes a step of reading in, a step of setting, a step of reducing, and a step of outputting. In the step of reading in, a raw data signal is read in, which encompasses camera raw data detected by the image sensor at a detection point in time. In the step of setting, a preprocessing algorithm for reducing the resolution of the camera raw data is set, using at least one setting signal. In the step of reducing, the resolution of the camera raw data is reduced, using the preprocessing algorithm set in the step of setting, to obtain a preprocessed camera signal which represents a preprocessed camera image. In the step of outputting, the preprocessed camera signal is output to an image processing unit.