In-Pixel Analog Vision SoC for Low-Power Parallel Image Processing
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Solution Overview
Problem
Existing multi-frame imaging systems face challenges in achieving high parallelism, reducing information flow, and minimizing power consumption for in-pixel image processing.
Innovation Solution
The implementation of in-pixel embedded analog image processing, where each pixel has its own processor, enabling high parallelism and reduced power consumption by performing computations within the pixel using analog computing elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional off-sensor digital processing is used, then computational accuracy is maintained, but power consumption increases and processing speed decreases
Solution Approach 1:
The patent transitions from digital domain processing to analog domain processing, representing a dimensional change in the computational domain. Analog computing elements perform image processing operations in the analog domain, which reduces power consumption while maintaining high processing speeds through parallel operations across multiple pixels simultaneously.
Solution Approach 2:
The patent replaces digital mechanical systems (transistors switching, data bus transfers, sequential processing) with analog computing elements that perform mathematical operations directly on continuous signals. This substitution eliminates the need for repeated digital-to-analog conversions and reduces the computational overhead associated with digital processing pipelines.
2Productivity
If in-pixel processing is implemented, then processing speed and parallelism increase, but device complexity increases
Solution Approach 1:
The patent divides the image processing functionality into segmented operations distributed across multiple pixels. Each pixel contains processing elements that can independently perform specific image processing tasks on local image data, enabling parallel processing without requiring a single complex centralized processor. This segmentation reduces the complexity burden on any single element while achieving high overall processing speed.
Solution Approach 2:
The patent implements universal processing elements within each pixel that can perform multiple image processing functions (e.g., convolution, differentiation, integration, thresholding) through reconfigurable analog circuitry. This multi-functionality reduces device complexity by eliminating the need for separate dedicated circuits for each processing operation, while still enabling high-speed parallel processing across the pixel array.
3Use of energy by moving object
If analog computing elements are used, then power consumption is reduced, but manufacturing precision requirements increase
Solution Approach 1:
The patent incorporates feedback mechanisms within the analog processing elements that automatically compensate for manufacturing variations and drift. By continuously monitoring and adjusting operating parameters based on actual performance, the system maintains accurate image processing results despite variations in analog component characteristics caused by manufacturing tolerances.
Solution Approach 2:
The patent employs parameter changes and calibration procedures that allow the analog computing elements to adapt to manufacturing variations. By adjusting operating parameters such as bias currents, reference voltages, and timing sequences, the system optimizes performance for specific manufacturing batches, thereby reducing the impact of manufacturing precision limitations on overall system performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient neighbor-in-space and neighbor-in-time processing, reducing power consumption and increasing processing speed while maintaining high accuracy in multi-frame imaging.
Implementation Method 1
Each in-pixel processing element includes a photodetector
Data Source
AI summary
An Artificial Intelligence (AI) multi-frame imaging System on Chip (SoC) incorporates in-pixel embedded analog image processing by performing analog image computation within a multi-frame image pixel. In embodiments, each in-pixel processing element includes a photodetector, photodetector control circuitry with at least three analog sub-frame storage elements, analog circuitry configured to process both neighbor-in-space and neighbor-in-time functions for analog data, and a set of north-east-west-south (NEWS) registers, each register interconnected between a unique pair of neighboring in-pixel processing elements to transfer analog data between the pair of neighboring in-pixel processing elements. In embodiments, the in-pixel embedded analog image processing device takes advantage of high parallelism because each pixel has its own processor, and takes advantage of locality of data because all data is located within a pixel or within a neighboring pixel.