Image Processing Apparatus Color Tone Conversion Weighting
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Solution Overview
Problem
Existing image processing systems face challenges in accurately reproducing color tones without reference color chart data, leading to inadequate color tone matching between different image output devices, especially when one device cannot output or provide the necessary reference data.
Innovation Solution
An image processing apparatus and system that perform color tone conversion using a converting degree parameter and weighted values to adjust the color tone conversion parameter, ensuring that the output result matches a reference output result by determining the degree of change needed for each pixel range based on color difference and distance from achromatic colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If color tone conversion is performed to match reference output results, then color tone reproduction accuracy is improved, but unnecessary conversion may occur when original image data already has appropriate color tones
Solution Approach 1:
The patent applies different conversion strategies to different regions of the color tone conversion parameter space. By dividing the color tone adjustment into multiple ranges and applying weighted values based on the degree of change needed, the system selectively converts only when necessary, preserving appropriate color tones while correcting inaccurate ones.
Solution Approach 2:
The patent introduces a converting degree parameter that quantifies the necessary color tone conversion for each pixel range. By using this parameter to determine weighted values, the system dynamically adjusts the conversion intensity, preventing unnecessary conversion when the original image data already has appropriate color tones while ensuring sufficient conversion when needed.
2Manufacturing precision
If complete color tone conversion is applied to all pixel ranges, then color tone matching is improved, but conversion precision for specific ranges is reduced
Solution Approach 1:
The patent segments the color tone conversion into multiple predetermined ranges based on the converting degree parameter. Each range is processed independently with appropriate weighted values, allowing precise control over conversion in specific regions while maintaining overall color tone matching accuracy.
Solution Approach 2:
Different weighted values are assigned to different pixel ranges based on their specific conversion needs. This local differentiation ensures that each range receives appropriate conversion precision tailored to its characteristics, rather than applying a uniform conversion approach.
3Adaptability or versatility
If manual color tone matching is performed when reference data is unavailable, then adaptability is improved, but processing time and complexity increase
Solution Approach 1:
The system performs self-calibration by automatically determining converting degree parameters and weighted values based on the available image data and output results. This eliminates the need for manual intervention and reference color chart data, allowing the system to adapt to different scenarios automatically without increasing processing time.
Solution Approach 2:
The patent dynamically adjusts conversion parameters based on the actual image data characteristics and output results. By using the converting degree parameter to determine weighted values, the system automatically optimizes color tone conversion without requiring manual setup or reference data, reducing both time and complexity.
Data Source
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AI summary
An image processing apparatus for performing color tone conversion on a predetermined original image data using a predetermined color tone conversion parameter, includes a converted image data generating unit that generates weight-applied converted original image data obtained by performing the color tone conversion by the color tone conversion parameter while applying weighted values, which is determined such that the lower the degree to be changed by the color tone conversion is, the smaller the value becomes, on the original image data for each of a predetermined range.