Image Correction Prioritization for Unified Multi-Object Quality
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Solution Overview
Problem
Existing image correction methods fail to achieve a sense of unity in image quality when correcting images containing multiple objects, leading to inconsistent results.
Innovation Solution
An information processing apparatus that determines, based on an analysis of object importance and prevalence in a set of images, which object to prioritize for correction, using a processor to adjust image settings accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the user adopts a configuration that corrects the image according to both or all of the two or more objects, then the correction covers all objects in the image, but the image cannot be corrected to achieve a sense of unity in image quality with the plurality of images
Solution Approach 1:
The patent segments the correction process by dividing images into groups based on their primary objects. Instead of applying a single correction to all objects in all images, the system creates separate correction settings for different object groups (e.g., images with people vs. images with landscapes). This allows each group to receive optimized correction while maintaining overall unity through coordinated correction strategies.
Solution Approach 2:
The patent implements dynamic correction by automatically selecting which objects to prioritize for correction based on image analysis. The system dynamically determines the primary object in each image and applies correction settings accordingly, rather than using a static approach that attempts to correct all objects uniformly. This dynamic selection enables unified image quality while adapting to the specific content of each image.
2Manufacturing precision
If the image is corrected according to a specific object, then the correction achieves unity for images containing that object, but other objects in the same image may not be properly corrected
Solution Approach 1:
The patent applies local quality by creating different correction settings for different object types. Instead of using a single global correction for all images, the system defines specific correction parameters tailored to each object category (e.g., skin tone adjustment for people, exposure adjustment for landscapes). This ensures that each object receives appropriate correction while maintaining overall image quality unity through coordinated application of these localized corrections.
Data Source
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AI summary
An information processing apparatus includes: a processor configured to: obtain plural images each including any of plural objects; and determine, based on an analysis result regarding the plural objects in the plural images, according to which of two or more objects, among the plural objects, included in an image the image is corrected.