Image Reading Device Super-Resolution Bayer Sensor
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Solution Overview
Problem
Conventional image reading devices struggle to accurately detect isolated points in halftone documents, leading to distorted gradation characteristics and poor image quality due to limitations in resolution and detection of black or white isolated points in highlight and shadow regions.
Innovation Solution
An image reading device equipped with a color filter array in a Bayer configuration and a hardware processor that reads documents using two groups of light receiving elements shifted by half pixels in the sub-scanning direction, interpolates and synthesizes image data to achieve twice the resolution, enabling accurate detection of isolated points and improved gradation characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If reading is performed with the upper limit resolution of 600 dpi, then the reading speed and productivity are maintained, but the detection precision of isolated points in highlight and shadow regions deteriorates
Solution Approach 1:
The patent applies super-resolution processing to generate image data at twice the resolution of the area sensor (e.g., 1200 dpi from 600 dpi sensor). This dimensional change in resolution enables accurate detection of isolated points in highlight and shadow regions while maintaining the original reading speed and productivity at 600 dpi.
Solution Approach 2:
The patent performs preliminary reading at 600 dpi using the area sensor, then applies super-resolution processing to generate high-resolution image data before final image processing. This preliminary action allows the system to maintain fast reading speed while subsequently achieving high detection precision through resolution enhancement.
2Reliability
If conventional image processing such as smoothing or edge enhancement is applied, then the distortion of gradation characteristics becomes less conspicuous, but the detection accuracy of isolated points remains insufficient
Solution Approach 1:
The patent generates image data at twice the resolution of the area sensor through super-resolution processing. This resolution enhancement allows isolated points to be accurately detected and represented, enabling subsequent image processing to correctly handle gradation characteristics without losing detection accuracy.
Solution Approach 2:
The patent replaces conventional image processing approaches (smoothing, edge enhancement) with a super-resolution-based approach. By generating high-resolution image data first, the system can accurately represent isolated points and perform appropriate image processing without the trade-offs inherent in conventional methods.
3Measurement precision
If the area of isolated points is smaller than one pixel or one isolated point extends over multiple pixels, then the reading resolution is insufficient to capture the isolated point accurately, but increasing resolution would require higher reading sensor capability
Solution Approach 1:
The patent uses super-resolution processing to generate image data at twice the resolution of the area sensor without requiring a higher-resolution sensor. This dimensional change in data resolution allows accurate capture of isolated points that are smaller than one pixel or extend over multiple pixels, while maintaining the original sensor specifications.
Solution Approach 2:
The patent creates a high-resolution copy of the original image data through super-resolution processing. This copied image data at twice the resolution enables accurate representation of isolated points without requiring the physical sensor to have higher resolution capabilities.
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
The solution allows for accurate detection of halftone dots, reducing distortion in gradation characteristics and enhancing image quality by interpolating and synthesizing high-resolution image data, effectively addressing the limitations of conventional image reading devices.
Implementation Method 1
an area sensor in which color filters of three colors of R, G, and B are arranged in a Bayer array and a light receiving amount is detected by a light receiving element for each color filter
Data Source
AI summary
An image reading device includes: an area sensor in which color filters of three colors of R, G, and B are arranged in a Bayer array and a light receiving amount is detected by a light receiving element for each color filter; and a hardware processor that: reads a document by using the light receiving elements in a first group in the area sensor, reads the document by using the light receiving elements in a second group in the area sensor, at a region shifted by ½ pixels in a sub-scanning direction from a reading region of the light receiving elements in the first group, and interpolates R-color read data and B-color read data using G-color read data and synthesizes image data having a resolution twice the resolution of the area sensor.