Optimal Exposure Time Projection via Pixel Intensity Analysis
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Solution Overview
Problem
Current methods for determining optimal exposure time in image capture are either labor-intensive and inaccurate, relying on trial-and-error or complex automatic exposure techniques that do not effectively consider user input or regional pixel intensity variations.
Innovation Solution
A computer-implemented method that captures multiple images at different exposure times, assesses pixels based on intensity thresholds, and determines a linear relationship to calculate an optimal exposure time that maximizes pixel intensity saturation, thereby generating a projected image with improved exposure settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trial-and-error image acquisition method is used to determine exposure time, then user can obtain some image data, but the process is labor-intensive and time-consuming requiring multiple image acquisitions
Solution Approach 1:
The system performs preliminary analysis on a first captured image to predict the optimal exposure time before actually capturing the final image. By calculating pixel intensity statistics and projecting saturation levels from the first image, the system determines the optimal exposure time in advance, eliminating the need for multiple trial acquisitions and directly producing the optimal image on the first attempt.
2Extent of automation
If complex automatic exposure methods are used, then exposure determination is automated, but the methods are inaccurate and do not effectively consider user input or regional pixel intensity variations
Solution Approach 1:
The system divides the image into multiple regions of interest and performs separate pixel intensity analysis on each region. By calculating statistics for each region independently and allowing user selection of specific regions, the system captures local variations in pixel intensity that global methods would average out, thereby improving the accuracy of exposure time determination for different areas of the image.
Solution Approach 2:
The system provides user feedback by displaying the first captured image with selectable regions and allowing the user to interactively choose which regions should be considered for optimal exposure determination. This feedback loop enables the user to guide the automated process toward their specific needs while maintaining the efficiency of automation.
3Device complexity
If optimal exposure time is determined based on entire image pixel intensity, then calculation is simplified, but it does not account for regional variations and user-specific targets
Solution Approach 1:
The system dynamically adapts the region of interest based on user input. Instead of using a fixed global calculation for the entire image, the system allows the user to selectively define which regions should be considered, making the exposure determination process adaptable to different user needs and image characteristics while maintaining reasonable computational complexity through efficient pixel intensity statistics calculation.
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 accurate determination of optimal exposure time, reducing the need for multiple image acquisitions and improving image quality by minimizing pixel saturation and under-exposure, thus enhancing the dynamic range of pixel intensities.
Implementation Method 1
The pixels are configured such that when light (photons) are detected by the pixels, each pixel provides an output in the form of an electrical signal that is proportional or related to the intensity of the detected light (photons)
Data Source
AI summary
Systems and methods generate a projected image at an optimal exposure time. Images are captured different exposure times. Pixels that satisfy an intensity threshold percentage for each image are selected. The intensity values of the selected pixels are then evaluated to determine whether the selected pixels are distributed above a lower intensity threshold and below an upper intensity threshold. The linear relationship is projected to determine an optimal exposure time that has an optimal exposure time duration that exceeds each exposure time duration associated with each of the captured images when the linear relationship exists between each of the captured images. A projected image associated with the optimal exposure time is generated from one or more of the captured images.