Weighted Brightness Exposure Control for Digital Imaging
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Solution Overview
Problem
Existing automatic exposure control methods in digital imaging devices, such as those using the 'Gray World Assumption', often result in over or under exposure in scenes with large bright or dark areas, lacking versatility and requiring complex scene-specific settings.
Innovation Solution
A method that computes the weighted average brightness of different brightness regions in an image, using techniques like brightness histograms or moving averages, to adjust exposure parameters independently of large bright or dark regions, ensuring universal adaptability across various scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic exposure control is designed based on Gray World Assumption using average brightness (AY) as the control parameter, then exposure control works well for scenes conforming to Gray World Assumption, but it generates over exposure or under exposure phenomena in special scenes with large bright or dark areas
Solution Approach 1:
The patent divides the image into multiple brightness regions (first brightness region with higher brightness, second brightness region with lower brightness) based on brightness distribution. By segmenting the image and calculating weighted average brightness separately for each region, the system can independently control exposure for different brightness areas, preventing both over-exposure in bright regions and under-exposure in dark regions while maintaining adaptability to various scene types.
2Reliability
If fuzzy logic control rules are applied to reduce the weight of non-subject area in AY computing, then under exposure or over exposure is reduced for subjects in typical positions, but the method requires building a scene pattern database and relies on presumption about subject position
Solution Approach 1:
The patent extracts and analyzes the brightness distribution characteristics of the image directly, calculating weighted average brightness for different brightness regions without requiring external scene pattern databases or fuzzy logic control rules. This approach obtains exposure control parameters directly from the image content itself, eliminating the need for complex pre-built databases and assumption-based control rules while maintaining high reliability in exposure control.
3Ease of manufacture
If exposure control relies on average brightness (AY) of the entire image, then the method is simple to implement, but it cannot handle scenes with large sections of bright or dark areas
Solution Approach 1:
The patent applies local quality by calculating weighted average brightness separately for different brightness regions (first brightness region with higher brightness, second brightness region with lower brightness) rather than using a single average brightness for the entire image. Each region is processed with appropriate weighting factors, allowing the exposure control to adapt to local brightness characteristics while maintaining overall simplicity through automated region-based processing.
Data Source
AI summary
The present invention discloses a method for acquiring automatic exposure control parameters and a method for controlling automatic exposure control parameters and an imaging device. The core idea is to take the brightness weighted average value obtained according to brightness distribution weighted statistics of the image as the exposure control parameter. Then through adjusting the weighted coefficient of pixels in different brightness regions, control the influence of the pixel concentrated brightness regions on the brightness average value. Because the brightness distribution is the basis for determining weighted statistics, the control method of the present invention is not influenced by the scene assumption. Rather it can be universally adapted to a variety of different scenes, and the exposure control effect is not influenced by the position of scenes in the actual bright region/dark region and block distribution.