Computational Sensor Grid for High Dynamic Range Imaging
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Solution Overview
Problem
Current image processing technologies face challenges in efficiently handling high dynamic range data and noise management with limited well-structured pixels/sensors, particularly in achieving precise and efficient processing of image data for computer vision applications.
Innovation Solution
Integration of a grid of processing elements with focal plane elements in an image sensor, where each focal plane element is treated as a local element and managed by a GPU for early data access and finer control, enabling local control of exposure times, noise management, and advanced algorithms like deep learning capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional centralized image processing is used, then processing capability is sufficient for basic tasks, but computation and power requirements increase for advanced algorithms and high dynamic range data
Solution Approach 1:
The patent divides the image sensor into multiple independent focal plane elements, each with its own processing elements. This segmentation allows parallel processing of image data at the pixel level, reducing the computational burden on centralized processors and lowering overall power requirements while maintaining high processing efficiency for advanced algorithms and high dynamic range data.
Solution Approach 2:
The patent introduces a new dimension of processing by integrating processing elements directly at the focal plane, moving computation from a centralized 2D processor to a distributed 3D architecture across the sensor array. This dimensional shift enables early data access and local processing, significantly reducing power consumption for complex operations.
2Reliability
If more pixels/sensors are used to capture high dynamic range data, then imaging quality improves, but device complexity and cost increase
Solution Approach 1:
The patent implements local quality control by giving each focal plane element independent processing capabilities and local control of exposure times. This allows different regions of the sensor to be optimized for different imaging conditions, achieving high dynamic range capture and improved image quality without requiring a uniform increase in sensor complexity across the entire device.
3Ease of operation
If centralized processing of image data is used, then data management is simplified, but early data access and local control are limited
Solution Approach 1:
The patent performs preliminary processing actions directly at the focal plane elements before data is transferred to centralized processors. Each focal plane element can access and process its own data immediately upon capture, enabling early data access and local control for tasks such as noise reduction, exposure adjustment, and feature detection, thereby reducing data access time while maintaining simplified centralized management for overall coordination.
Data Source
AI summary
A system and method for controlling characteristics of collected image data are disclosed. The system and method include performing pre-processing of an image using GPUs, configuring an optic based on the pre-processing, the configuring being designed to account for features of the pre-processed image, acquiring an image using the configured optic, processing the acquired image using GPUs, and determining if the processed acquired image accounts for feature of the pre-processed image, and the determination is affirmative, outputting the image, wherein if the determination is negative repeating the configuring of the optic and re-acquiring the image.