Image Color Correction via Region-Specific Parameter Segmentation
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Solution Overview
Problem
Existing image enhancement technologies focus primarily on the color of human faces, leading to unnatural color enhancements in other regions of images.
Innovation Solution
An image processing device that analyzes and distinguishes between a region with a human face and other regions, calculating separate parameters for each to enhance color tone appropriately, using a weighted average based on target values and regional proportions to maintain natural appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color enhancement is performed based only on face region parameters, then face color accuracy is improved, but natural appearance of other regions deteriorates
Solution Approach 1:
The patent applies local quality by calculating different color parameters for different regions: face-specific parameters (average color, standard deviation) for the face region, and background parameters for non-face regions. The enhancement then applies different target chromaticities to different regions based on their local characteristics, ensuring face accuracy while maintaining natural appearance elsewhere.
Solution Approach 2:
The patent segments the image into face region and background region, determining parameters separately for each segment. The face region gets enhanced using face-specific parameters, while the background region is handled separately to preserve its natural appearance, thus resolving the contradiction between face accuracy and overall naturalness.
2Device complexity
If uniform color enhancement is applied to the entire image, then processing simplicity is improved, but regional color accuracy deteriorates
Solution Approach 1:
Instead of uniform enhancement, the patent implements local quality by calculating region-specific parameters (face average color, face standard deviation, background color) and applying different enhancement strategies to different regions. This maintains regional color accuracy while managing complexity through systematic parameter calculation.
Solution Approach 2:
The patent segments the image processing into distinct regions (face and background) with separate parameter calculations and enhancement applications. This segmentation approach improves regional color accuracy by treating each region according to its specific characteristics rather than applying a single uniform enhancement to the entire image.
Data Source
AI summary
A technology is provided whereby correction may be carried out appropriately for both a person's face and other portions of an image, when performing color correction for image data of a photographic image in which a person appears. A process such as the following is carried out during color correction of image data of a photographic image. First, the image data of the photographic image is analyzed, and a first region which is part of the photographic image and in which a person's face is present is determined. Then, on the basis of the portion corresponding to the first region of the image data, a first parameter relating to color is calculated. On the basis of part of the image data corresponding to a second region which is part of the photographic image but different from the first region, a second parameter relating to color is calculated. The color tone of the data is then corrected on the basis of the first and second parameters.