Image Sensor Parameter Control for Luminance Consistency
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Solution Overview
Problem
Existing methods for controlling image sensors fail to effectively manage luminance values across multiple image sensors, leading to inconsistencies in image quality and exposure bracketing.
Innovation Solution
A method that involves receiving images from multiple image sensors, calculating feature values such as luminance, saturation, and signal-to-noise ratio, and generating comparison results to control parameters like analog gain and exposure time, ensuring consistent or varied luminance values across sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple image sensors are controlled to obtain images with the same luminance value, then luminance similarity is improved, but exposure control flexibility deteriorates
Solution Approach 1:
The patent implements dynamic control of image sensor parameters by allowing the system to switch between different operational modes: a first mode where multiple sensors are controlled to capture images with the same luminance value for high luminance similarity, and a second mode where sensors are controlled to capture images with different luminance values for exposure bracketing. This dynamic adaptability resolves the contradiction by making the system flexible enough to adjust its control strategy based on the desired outcome.
2Adaptability or versatility
If multiple image sensors are controlled to obtain images with different luminance values, then exposure bracketing is improved, but luminance similarity deteriorates
Solution Approach 1:
The system dynamically adjusts the control mode of multiple image sensors based on operational requirements. When exposure bracketing is needed, the system switches to a second control mode where sensors capture images with different luminance values, thereby improving exposure bracketing capability while temporarily accepting reduced luminance consistency. This dynamic switching resolves the contradiction by allowing the system to optimize for different goals at different times.
3Measurement precision
If image sensor parameters are controlled manually, then control precision is improved, but operation complexity increases
Solution Approach 1:
The patent implements self-service control where the processing circuit automatically determines and adjusts image sensor parameters based on analysis of captured images. The system calculates luminance values of captured images, compares them against target values, and autonomously adjusts exposure parameters without requiring manual intervention. This self-adjusting mechanism maintains high control precision while significantly reducing operational complexity.
Solution Approach 2:
The system employs feedback control by continuously monitoring the luminance values of images captured by multiple sensors and using this information to adjust subsequent exposure parameters. The processing circuit calculates the luminance of captured images, compares it with target luminance values, and uses this feedback to determine optimal exposure settings for the next capture cycle, thereby achieving precise control through automated closed-loop regulation.
Data Source
AI summary
A method of controlling parameters for image sensors includes; receiving a first image and a second image, calculating first feature values related to the first image and second feature values related to the second image; generating comparison results by comparing the first feature values of fixed regions and first variable regions of the first image with the second feature values of fixed regions and first variable regions of the second image, and controlling at least one parameter on the basis of the comparison results.