Image Processing Apparatus Color Conversion Model Classification
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Solution Overview
Problem
Existing image processing technologies face challenges in preparing accurate color conversion characteristics due to contradictions arising from images captured with varying capture settings, leading to reduced precision in color conversion models when using only capture setting information.
Innovation Solution
An image processing apparatus that uses both capture setting information and the lightness of the background region to classify and prepare color conversion models, ensuring accurate color conversion by selecting the appropriate model based on the specific capture setting and background lightness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color conversion characteristics are prepared using only capture setting information, then the classification is simple, but contradictions occur in color conversion characteristics when images are captured with varying capture settings
Solution Approach 1:
The patent segments the classification of teacher data by dividing it into multiple stages: first classification by capture setting information, then further classification by background lightness within each capture setting group. This hierarchical segmentation resolves contradictions by creating finer-grained categories without overwhelming complexity
Solution Approach 2:
The patent adds a new dimension (background lightness) to the classification system beyond the traditional capture setting information. This dimensional expansion allows the system to differentiate between images with same capture settings but different lighting conditions, eliminating color conversion contradictions
2Adaptability or versatility
If color conversion characteristics are prepared for each capture setting information, then the adaptation to different capture conditions is improved, but contradictions arise when some images match capture environment while others do not
Solution Approach 1:
The patent applies local quality by treating different background lightness levels within the same capture setting group differently. Instead of applying a uniform color conversion characteristic to all images with the same capture settings, the system selectively applies different characteristics based on the specific background lightness, improving both adaptability and reliability
3Measurement precision
If multiple classification criteria are used to prepare color conversion models, then the accuracy of color conversion is improved, but the processing complexity increases
Solution Approach 1:
The patent segments the model preparation process into distinct phases: first grouping by capture setting information, then further dividing by background lightness. This segmentation makes the complex multi-criteria classification more manageable and systematic, reducing the perceived complexity while maintaining high accuracy
Data Source
AI summary
An image processing apparatus includes a processor. The processor is configured to execute a program to input, to a learning unit, capture setting information that is used to capture an image before color conversion, a lightness of a background region of the image before the color conversion, and a set of the image before the color conversion and an image after the color conversion, and prepare color conversion characteristics for performing color conversion on an image in accordance with the capture setting information and the lightness of the background region.