Dual Camera Imaging Condition Detection via Luminance Analysis
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Solution Overview
Problem
Existing dual-camera configurations for image capture face challenges in automatically detecting imaging conditions, particularly under low-light conditions, due to the large exposure gap between black-white and color cameras, leading to unstable lighting detection and unreliable post-processing results for non-professional users.
Innovation Solution
A method and apparatus that determine imaging lightness based on luminance distribution in a color image and exposureness by analyzing highlighted regions in a black-white image, using texture information from corresponding regions in the color image to accurately estimate exposure levels, enabling adaptive image fusion processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional lighting detection through reading camera hardware parameters is used, then the detection process is simple, but the detecting result is unstable due to extreme sensitivity to noise and lack of dedicated hardware in all cameras
Solution Approach 1:
The patent introduces an intermediary detection approach by using the color camera's captured image data as a mediator to infer lighting conditions. Instead of directly reading unstable hardware parameters, the system analyzes luminance distribution and histogram characteristics of the color image to determine imaging lightness, thereby achieving stable lighting detection without requiring dedicated hardware in all cameras.
Solution Approach 2:
The patent replaces the mechanical/hardware-based detection method (reading camera hardware parameters) with an image-processing-based method. By substituting direct hardware parameter reading with analysis of luminance distribution and histogram characteristics from captured images, the system achieves more reliable lighting detection that is less sensitive to noise and hardware variations.
2Measurement precision
If manual setting of imaging condition is required, then the detection accuracy can be high, but user burden significantly increases and user experience is dampened
Solution Approach 1:
The patent implements self-service by enabling the system to automatically detect and determine imaging conditions without user intervention. The color camera automatically captures images, the processor analyzes luminance distribution and histogram characteristics, and the system autonomously determines imaging lightness and exposureness, thereby maintaining high detection accuracy while eliminating user burden.
Solution Approach 2:
The patent changes the detection parameters from manual user inputs to automatically extracted image features. By analyzing luminance distribution, histogram characteristics, and texture information from captured images, the system transforms the detection process into an automated parameter-based approach that maintains precision while improving ease of operation.
3Manufacturing precision
If super resolution processing is applied under normal light condition, then the resolution of fused image is enhanced, but under low-light condition the processing cannot be performed due to large brightness gap between two cameras
Solution Approach 1:
The patent applies dynamics by making the image processing approach adaptive to different lighting conditions. The system dynamically selects processing methods based on detected imaging conditions: super resolution processing is applied under normal light conditions to enhance resolution, while alternative processing approaches are used under low-light conditions where large brightness gaps exist between cameras, thereby achieving both high resolution quality and processing adaptability.
Solution Approach 2:
The patent changes processing parameters based on detected imaging conditions. By monitoring luminance distribution and histogram characteristics, the system adjusts processing parameters to select appropriate fusion methods for different lighting scenarios, enabling super resolution under normal conditions while switching to brightness-compensated fusion under low-light conditions.
Data Source
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AI summary
Embodiments of the present invention relate to a method and apparatus for detecting an imaging condition. In one embodiment, there is provided a method for detecting an imaging condition. The method comprises: determining, based on luminance distribution in a first image of a scene, imaging lightnessof the first image, the first image being captured by a first camera; determining, based on detection of a highlighted region in a second image of the scene, imaging exposureness of the second image, the second image being captured by a second camera, the first image and the second image being captured under a same or similar imaging condition, an exposure amount of the first camera being lower than an exposure amount of the second camera. There is also disclosed a relevant apparatus, electronic device, and a computer program product.