Image Processing Apparatus Night Scene Under-Exposure Classification
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Solution Overview
Problem
Existing image processing methods fail to accurately distinguish between night scene and under-exposure categories, leading to inadequate correction intensity for under-exposed images, as they often classify both as front light scenes, resulting in insufficient brightening of dark portions.
Innovation Solution
An image processing apparatus that divides images into areas, calculates feature amounts, and determines whether each area is a night scene or under-exposure category, allowing for specific correction processing based on the entire image category determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If luminance difference between center and circumference sections is used to determine scene type, then backlight and front light scenes can be distinguished, but night scene and under-exposed images cannot be differentiated, resulting in insufficient correction for under-exposed images
Solution Approach 1:
The image is divided into multiple sections (center and circumference) for separate luminance analysis. This segmentation allows the system to evaluate different regions independently and combine their results to distinguish between night scenes and under-exposed images, resolving the limitation of using only center-circumference luminance difference.
Solution Approach 2:
The patent introduces additional parameters beyond center-circumference luminance difference, including average luminance of the entire image and luminance distribution characteristics. By changing and expanding the parameter set used for scene classification, the system can accurately differentiate between night scenes and under-exposed images, enabling appropriate correction processing for each type.
2Ease of manufacture
If the same correction intensity is applied to both night scene and under-exposed images, then processing simplicity is maintained, but correction quality deteriorates for under-exposed images
Solution Approach 1:
The system implements feedback by calculating scene type accuracy based on multiple parameters and using this information to determine appropriate correction intensity. The correction amount is adjusted according to the determined scene type, ensuring that under-exposed images receive stronger correction while night scenes receive minimal correction, thereby maintaining high correction quality without excessive complexity.
3Manufacturing precision
If manual correction processing is performed for each image, then correction accuracy can be optimized, but processing time increases significantly for large volumes of images
Solution Approach 1:
The patent implements automatic scene type determination and correction amount calculation based on image parameters, enabling the system to self-service without manual intervention. The automated process maintains high correction accuracy by using multiple parameters to distinguish between night scenes and under-exposed images, while simultaneously achieving high processing speed suitable for batch processing large volumes of images.
Data Source
AI summary
An image processing apparatus includes a division unit configured to divide an image into a plurality of areas, a calculation unit configured to calculate a feature amount for each division area, an area category determination unit configured to determine for each division area at least a night scene category or an under-exposure category based on the calculated feature amount, an entire category determination unit configured to determine a category of the entire image based on the result of category determination, and a processing unit configured to perform correction processing on the image based on the result of category determination by the entire category determination unit.