Object-Based Color Adjustment Using CIELAB Quantization
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Solution Overview
Problem
Global color adjustment in image editing applications often results in unnatural colors for natural objects, making the images appear unrealistic, as it affects all objects uniformly, leading to inefficient and time-consuming selective adjustments to correct these errors.
Innovation Solution
An image editing system that quantizes a color space into classes representing pairs of channel values, uses an object detector to segment objects, and adjusts color parameters based on object-specific ranges, allowing selective adjustments through a user interface with adjusters that reflect the ranges of color parameters for each object, ensuring natural colors are maintained for objects during global adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If global color adjustment is applied to the entire image, then color parameter adjustment efficiency is improved, but natural objects acquire unnatural colors
Solution Approach 1:
The patent applies local quality by determining object-specific color parameter ranges for different regions of the image. The system segments the image into multiple objects and calculates separate color parameter ranges for each object based on their natural color characteristics. This allows the adjustment system to apply color changes selectively to objects whose color ranges include the adjusted value, preserving natural colors for objects that should not be changed while still providing efficient global adjustment capability.
2Manufacturing precision
If selective adjustment of objects is performed to maintain natural colors, then color accuracy of natural objects is improved, but editing time increases
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing color parameter ranges for each object in the image before any user adjustment is made. The system analyzes the natural color characteristics of each object and determines the minimum and maximum values for color parameters such as hue, saturation, and lightness. This preliminary analysis enables the system to automatically and instantaneously determine which objects should be adjusted when a user modifies a color parameter, eliminating the need for time-consuming manual selective adjustment while maintaining color accuracy.
3Ease of operation
If global color adjustment is used, then ease of operation is improved, but realism of the adjusted image deteriorates
Solution Approach 1:
The patent applies self-service by enabling the adjustment system to automatically determine which objects should be modified based on their pre-calculated color parameter ranges. When a user adjusts a color parameter, the system autonomously evaluates each object's range against the adjusted value and applies the change only to appropriate objects without requiring user intervention. This self-service mechanism maintains ease of operation with simple global adjustment controls while ensuring realism by preventing unnatural color changes to objects whose ranges exclude the adjusted value.
Data Source
AI summary
In implementations of object-based color adjustment, an image editing system adjusts hue and saturation of a digital image so that objects in the digital image do not appear unnatural. The image editing system quantizes a CIELAB color space into classes that represent pairs of a and b channel values. The image editing system determines probabilities that pixels of a digital image belong to each of the classes, and based on the probabilities, determines a range of hue and a range of saturation for each pixel. An object detector segments objects in the digital image to determine ranges of hue and saturation for each segmented object. The image editing system selectively adjusts the hue and saturation for objects of the digital image based on whether the hue and saturation range for the object include a value of hue and saturation, respectively, selected in a user interface.