Photoelectric Conversion Layout With Parallel AI Signal Processing
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Solution Overview
Problem
The existing photoelectric conversion apparatuses with a single processing unit based on a learned model face limitations in processing speed and load, which can lead to decreased performance in advanced signal processing tasks.
Innovation Solution
The apparatus includes multiple AI processing units with different learned models, each processing signals from photoelectric conversion units with distinct optical properties, allowing for parallel processing and optimized signal handling for various color filters, thereby increasing processing speed and reducing heat generation and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single processing unit is used to process all photoelectric conversion units, then device complexity is reduced, but processing speed and productivity decrease
Solution Approach 1:
The patent divides the single processing unit into multiple processing units (first processing unit and second processing unit), each dedicated to processing signals from specific photoelectric conversion units. This segmentation enables parallel processing of signals from different photoelectric conversion units, thereby increasing processing speed and productivity while maintaining manageable device complexity through functional specialization.
2Temperature
If a single processing unit processes all signals, then device complexity is minimized, but the processing unit experiences high load and heat generation
Solution Approach 1:
The patent segments the processing workload by creating multiple processing units that handle signals from different photoelectric conversion units separately. This distribution of processing tasks reduces the computational load on each individual processing unit, thereby reducing heat generation and power consumption while maintaining overall system functionality.
3Measurement precision
If different learned models are used for different photoelectric conversion units, then signal processing accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by assigning different learned models to different processing units based on the specific characteristics of the photoelectric conversion units they serve. Each processing unit is optimized with a learned model tailored to its associated photoelectric conversion units, improving signal processing accuracy for each specific case while maintaining overall system manageability through this localized optimization approach.
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 configuration enhances processing speed, reduces heat and power consumption, and enables optimal processing for each color filter, leading to improved image quality and accuracy in image processing tasks.
Implementation Method 1
a photoelectric conversion region 101 in which a plurality of photoelectric conversion units are arranged
Data Source
AI summary
A photoelectric conversion apparatus has a first filter arranged so as to correspond to a first photoelectric conversion unit and a second filter arranged so as to correspond to a second photoelectric conversion unit. The photoelectric conversion apparatus has a first processing unit configured to process an output signal from the first photoelectric conversion unit and having a first learned model, and a second processing unit configured to process an output signal from the second photoelectric conversion unit and having a second learned model different from the first learned model.