Image Processing Device Hue-Specific Color Correction
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Solution Overview
Problem
Existing image processing technologies require base image data to correct object image data, limiting the ability to make corrections without this data.
Innovation Solution
A multi-function device with a first determination unit to calculate a representative value for specific pixels within a particular hue range, a second determination unit to set a target value based on user input, and a correction unit to adjust pixel values in the object image data to approach the target value, allowing for color correction within a specific hue range without using base image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If base image data is used to correct object image data, then color correction accuracy is improved, but the complexity of the system increases due to the requirement of additional base image data
Solution Approach 1:
The patent extracts only the necessary color information from the object image data itself by identifying specific pixels within a predetermined hue range and calculating their representative values, rather than requiring external base image data. This extraction approach maintains correction accuracy while eliminating the complexity of managing additional data sources.
Solution Approach 2:
The system performs self-correction by using the object image data itself as the source for determining correction parameters. The representative value calculation and target value determination are derived entirely from the input image, allowing the system to correct its own color issues without external assistance or base images.
2Manufacturing precision
If all hues in object image data are corrected, then overall image quality is improved, but the processing time increases
Solution Approach 1:
The patent segments the color correction task by focusing only on pixels within a predetermined hue range (such as blue sky) rather than processing all hues in the image. This segmentation allows the system to achieve effective color correction for specific regions while significantly reducing the total number of pixels that require processing.
Solution Approach 2:
The system applies different processing strategies to different regions of the image based on their hue characteristics. By identifying and treating only the pixels within the predetermined hue range with specialized correction algorithms, the system optimizes processing efficiency for specific color regions without unnecessarily processing other areas.
3Productivity
If a representative value calculation is performed on specific pixels within a predetermined hue range, then processing speed is improved, but the color correction accuracy may be reduced
Solution Approach 1:
The system uses feedback by calculating the representative value from the actual pixel values within the target hue range and then using this representative value to determine the target value for correction. This feedback loop ensures that the correction is based on the actual color characteristics present in the image, maintaining accuracy while using efficient representative value calculations.
Solution Approach 2:
The patent changes the parameter representation by working with representative values that summarize the color characteristics of multiple pixels. By transforming individual pixel data into representative values and then using these to guide correction, the system achieves both computational efficiency and color accuracy through parameter transformation.
Data Source
AI summary
An image processing device may create corrected image data by correcting target image data. The image processing device may determine a representative value which represents specific pixels in the object image data, determine a target value based on the representative value and a degree of correction designated by a user, and correct a value of each particular pixel included in the object image data such that the value of the each particular pixel approaches the target value. The each particular pixel may be included in a surrounding area of the representative value.