Image Processing Apparatus Color Shift Correction
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Solution Overview
Problem
Higher reading resolutions in color scanners increase the number of chromatic color pixels due to color shifts, leading to edge blurring and expanded ranges of color-shifted pixels, which conventional correction methods struggle to address effectively, especially in originals with blurred edges like those printed by inkjet systems.
Innovation Solution
An image processing method and apparatus that detect chromatic color pixels between achromatic pixels and correct them to achromatic color by shifting pixel positions, allowing for repeated color shift correction without complicating processing, even with expanded ranges of color-shifted pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If reading resolution is increased to improve image detail, then manufacturing precision is improved, but the number of chromatic color pixels due to color shifts increases, worsening image quality
Solution Approach 1:
The patent segments the color shift correction problem by identifying and treating different types of chromatic pixels (first chromatic pixels between achromatic pixels, second chromatic pixels adjacent to first chromatic pixels) separately. This segmentation allows targeted correction of color shifts at different locations and with different characteristics, effectively reducing the number of chromatic color pixels even at high reading resolutions.
Solution Approach 2:
The patent changes the parameter of chromatic pixel correction by using luminance value comparisons to identify achromatic pixels and by adjusting the correction approach based on the position and characteristics of chromatic pixels. This parameter-based approach enables effective color shift correction that maintains image quality at high reading resolutions.
2Reliability
If conventional color shift correction methods are used, then some color shifts are corrected, but the processing becomes complicated and memory registration requirements increase when dealing with expanded ranges of color-shifted pixels
Solution Approach 1:
The patent extracts and focuses on the essential characteristics of chromatic pixels by identifying them through luminance value comparisons with adjacent pixels. This extraction approach simplifies the correction process by concentrating on key identifying features rather than requiring complex pattern matching or extensive memory registration, thereby reducing processing complexity while maintaining correction effectiveness.
Solution Approach 2:
The patent implements a self-service correction mechanism where the system automatically identifies and corrects chromatic pixels based on their luminance characteristics and positional relationships. This self-service approach eliminates the need for manual intervention or complex external processing, reducing overall system complexity while effectively handling expanded ranges of color-shifted pixels.
3Reliability
If conventional color shift correction methods are used, then some color shifts are corrected, but edge blurring impact on image quality is not minimized
Solution Approach 1:
The patent applies local quality correction by treating different regions of the image differently based on their characteristics. First chromatic pixels between achromatic pixels are corrected using one approach, while second chromatic pixels adjacent to first chromatic pixels are corrected using another approach. This localized correction strategy preserves edge sharpness by applying appropriate corrections only where needed, minimizing the impact of edge blurring on image quality.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables effective color shift correction across various resolutions and original types, reducing the need for complex processing and memory registration, and minimizing the impact of edge blurring on image quality.
Implementation Method 1
The light source of the lighting device is LEDs that are capable of illuminating at emission wavelengths corresponding to Red (R), Green (G), and Blue (B) light. An original is read by the line-shaped image sensor receiving reflected light from the original
Implementation Method 2
A color scanner includes a carriage that is movable in a predetermined direction and equipped with a lighting device and an image sensor... An original is read by the line-shaped image sensor receiving reflected light from the original
Data Source
AI summary
An image processing apparatus reads an image on an original and generates lines of data by causing a carriage to perform scanning, then by referring to the data, detects chromatic color pixels that exist between two achromatic color pixels, being first and second achromatic color pixels, from among pixels in the image that has been read in the scanning direction of the carriage, and determines one of the detected chromatic color pixels as a pixel of interest and corrects the pixel of interest to an achromatic color pixel while shifting the position of the pixel of interest pixel-by-pixel N times from a pixel position adjacent to the first achromatic color pixel in a direction toward the second achromatic color pixel.