Automatic Exposure Control Using Histogram Equalization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern cameras have a limited dynamic range, making it difficult to automatically determine optimal exposure parameters, resulting in overexposed or underexposed images.
Innovation Solution
A method that involves receiving image values, determining their distribution, equalizing them to enhance the image values, and adjusting exposure parameters such as shutter speed, aperture, and gain to optimize image capture, using a box-constrained least squares method and photopic luminous efficiency function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual process is used to determine correct exposure, then image quality can be optimized, but operation complexity and time consumption increase
Solution Approach 1:
The system enables automatic exposure determination by having the camera system self-adjust exposure parameters based on analyzing the captured image's histogram distribution, eliminating the need for manual intervention while maintaining accurate exposure control
Solution Approach 2:
The system captures an initial image, analyzes its histogram distribution, compares it against a target distribution, and uses this feedback to calculate and apply corrected exposure parameters for subsequent images, creating a closed-loop control system that automatically optimizes exposure
2Ease of operation
If automatic exposure control is implemented, then ease of operation improves, but measurement precision of optimal exposure deteriorates
Solution Approach 1:
The system uses histogram feedback from captured images to iteratively refine exposure parameters, comparing actual image value distributions against target distributions to automatically determine optimal exposure settings with high precision
Solution Approach 2:
The system performs preliminary exposure capture and histogram analysis to determine the relationship between image values and exposure parameters before final image capture, using this pre-established data to calculate precise exposure corrections
3Illumination intensity
If exposure parameters are adjusted to capture more light in dark scenarios, then image brightness improves, but risk of overexposure in bright areas increases
Solution Approach 1:
The system analyzes the histogram distribution across different brightness regions separately, applying targeted exposure adjustments that preserve detail in both dark and bright areas by treating different luminance ranges with appropriate correction strategies
Solution Approach 2:
The system dynamically adjusts exposure parameters based on the actual content and lighting conditions of each scene by analyzing histogram distribution, allowing flexible adaptation to varying brightness scenarios while maintaining overall exposure consistency
Data Source
AI summary
This disclosure concerns the determination of improved exposure parameters of an image capturing device, such as a multi-spectral or hyper-spectral camera. A processor receives or determines image values for multiple points of an image and receives first one or more exposure parameters that were used to generate the image values. The processor then determines a distribution of the image values. For each point of the image data the processor then determines an enhanced value by equalizing the distribution of the image values. Finally, the processor determines the one or more improved exposure parameters of the image capturing device, such that the one or more improved exposure parameters adjust the received or determined image values towards the enhanced image values. When the exposure parameters are used for capturing a further image, the further image will be enhanced.