ISP Day-Night Detection Using White Balance Deviation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing camera systems struggle to seamlessly transition between day mode and night mode due to reliance on ambient light sensors, which can lead to inaccurate transitions and increased manufacturing costs.
Innovation Solution
The implementation of an image signal processor (ISP)-based day/night mode detection system, which uses automatic white balance statistics and adaptive brightness thresholds to determine when to switch between modes, thereby minimizing flicker and improving color accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ambient light sensors are used for day-night mode detection, then the camera can detect light intensity, but the transition accuracy deteriorates and manufacturing cost increases
Solution Approach 1:
The patent repurposes the existing image signal processor (ISP), originally designed for image processing, to perform day-night mode detection. By utilizing the ISP's existing light intensity calculation capabilities through white balance statistics (R/G and B/G ratios), the system eliminates the need for dedicated ambient light sensors while improving transition accuracy. The ISP analyzes the captured image data to determine whether to switch between day and night modes, making the system more cost-effective and accurate simultaneously.
2Productivity
If fixed brightness thresholds are used for mode transition, then the implementation is simple, but flicker occurs during transition
Solution Approach 1:
The patent implements dynamic brightness thresholds that adapt to different illuminant conditions. Instead of using fixed thresholds, the system calculates adaptive thresholds based on the current white balance statistics and scene characteristics. This dynamic adjustment prevents flicker by ensuring thresholds are appropriate for each lighting condition, while maintaining fast transition response through real-time calculation based on existing image data.
Solution Approach 2:
The system changes the brightness threshold parameter dynamically based on illuminant type and scene conditions. By adjusting the threshold values according to the specific lighting environment (e.g., different thresholds for incandescent, fluorescent, or natural light), the system achieves stable transitions without flicker while maintaining quick response to actual lighting changes.
Data Source
AI summary
Approaches are described for image signal processor day-night detection. An exemplary approach for a camera with an infrared light source involves determining a brightness value for image data based on an average luma value for the image data, determining white balance data for the first image data, and determining, based on the white balance data for the image data and white balance data for the infrared light source, a deviation value for the image data. A transition from night mode to day mode can be effected based on comparing the brightness value for the image data to a first threshold, and comparing the deviation value for the image data to a second threshold.