Analog Domain Feature Extraction for Imaging Systems
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Solution Overview
Problem
Conventional imaging systems require excessive digital signal processing and power consumption for feature extraction in image sensors, which can be inefficient and power-intensive, especially when dealing with large pixel arrays and high-resolution image capture.
Innovation Solution
Implementing an analog domain feature extraction method using stacked imaging systems with dedicated analog processing circuits, allowing for efficient detection of features in regions of interest without the need for full-resolution digital processing, and utilizing variable integration times and weights for pixel values to perform convolution operations directly at the pixel level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-resolution digital processing is used for feature extraction, then measurement precision is improved, but use of energy increases and productivity decreases
Solution Approach 1:
The patent divides the pixel array into multiple regions of interest (ROIs), each processed independently by dedicated analog processing circuits. This segmentation allows feature extraction to be performed only on relevant portions of the image at high precision, while other regions use lower-resolution processing, thereby reducing overall power consumption while maintaining feature extraction accuracy where needed.
Solution Approach 2:
The patent replaces digital signal processing with analog domain processing for feature extraction operations. By performing convolution and feature detection directly in the analog domain using continuous voltage signals rather than digital binary processing, the system achieves comparable measurement precision with significantly reduced power consumption and bandwidth requirements.
2Measurement precision
If full-resolution digital processing is used for feature extraction, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The pixel array is segmented into multiple regions of interest, each with its own dedicated analog processing circuit. This parallel segmentation enables simultaneous feature extraction across multiple ROIs, dramatically improving processing efficiency and throughput while maintaining high measurement precision in each region.
Solution Approach 2:
The patent substitutes digital processing operations with analog domain operations that can be performed continuously and in parallel. Analog convolution and feature detection circuits process multiple regions simultaneously without the sequential bottlenecks of digital processing, thereby enhancing productivity while preserving feature extraction accuracy.
3Use of energy by moving object
If analog domain feature extraction is implemented, then use of energy decreases and productivity increases, but device complexity increases
Solution Approach 1:
The patent merges multiple functions into integrated analog processing circuits that perform pixel binning, convolution, and feature extraction simultaneously within the same hardware block. By combining these operations in the analog domain rather than implementing them as separate digital processing stages, the system reduces overall device complexity while achieving lower power consumption and higher processing efficiency.
Solution Approach 2:
The patent transitions from two-dimensional pixel spatial arrangement to three-dimensional stacked architecture, placing analog processing circuits in dedicated layers beneath the pixel array. This dimensional reorganization allows complex analog processing functions to be implemented without increasing the footprint of the pixel array, managing device complexity through vertical integration rather than horizontal expansion.
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 reduces power consumption and bandwidth requirements by performing feature extraction and convolution operations in the analog domain, enabling efficient detection of objects and scene information with reduced digital data transfer and processing, while maintaining high-resolution image capture capabilities.
Implementation Method 1
The pixel circuit may include a photodiode PD that generates an image signal in response to incoming light
Data Source
AI summary
Imaging circuitry may include circuits for implementing feature extraction in the analog domain. The imaging circuitry may include pixels configured to generate pixel values. The pixel values may then be weighted using variable charge integration times, variable resistors in the readout path, and/or variable switch on times in the readout path. The weighted pixels values may be binned and combined to obtain an output neuron voltage for at least one layer in a neural network. Performing feature extraction in the analog domain for each layer of results in the neural network saves power and area by avoiding the need to move data around to conventional digital memories.