Pixel Interpolation Using Dynamic Template Sizing for Halftone Accuracy
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Solution Overview
Problem
Current pixel interpolation methods in scanner devices, particularly those using contact image sensors (CIS), face challenges in accurately interpolating missing or incorrect pixel values, especially in halftone dot regions with high screen ruling, due to fixed template sizes and search ranges, leading to decreased interpolation accuracy and image quality.
Innovation Solution
An image processing apparatus dynamically determines the template size and search range for pattern matching based on the periodicity of the image region, using a cycle estimating unit and partial region periodicity determining unit to select the appropriate interpolation method, either pattern matching or interpolating, to optimize pixel value estimation for the target pixel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed template size and search range are used in pattern matching, then the interpolation process is simple and fast, but the interpolation accuracy decreases, especially in halftone dot regions with high screen ruling
Solution Approach 1:
The patent applies dynamics by making the template size and search range adjustable rather than fixed. The system dynamically determines the appropriate template size and search range based on the periodicity of the image region, allowing the interpolation process to adapt to different image characteristics such as halftone dot patterns with varying screen ruling frequencies.
Solution Approach 2:
The patent changes the parameters of the interpolation process by determining the template size and search range based on the periodicity of the image region. This parameter change allows the system to optimize the interpolation accuracy for different image types, particularly improving performance in halftone dot regions with high screen ruling while maintaining simplicity in other regions.
2Measurement precision
If a large template size and extensive search range are used in pattern matching, then the reproduction of high-frequency components improves, but the processing time increases
Solution Approach 1:
The system dynamically adjusts the template size and search range based on the periodicity detection results. For regions with high-frequency patterns like halftone dots, the system uses larger templates and extended search ranges to improve reproduction accuracy. For regions with lower frequency variations, the system uses smaller templates and reduced search ranges, thereby reducing processing time while maintaining accuracy where needed.
Solution Approach 2:
The patent applies local quality by tailoring the template size and search range to the specific characteristics of each image region. Instead of using a uniform large template for the entire image, the system adapts the parameters locally based on the periodicity of each region, improving the reproduction of high-frequency components in halftone dot regions while avoiding unnecessary processing time in other areas.
3Productivity
If linear interpolation is used, then the processing is fast and simple, but the accuracy deteriorates in regions with severe density changes like halftone dot regions
Solution Approach 1:
The system changes the interpolation method based on the periodicity of the image region. When periodicity is detected (indicating halftone dot regions with regular patterns), the system switches from simple linear interpolation to pattern matching with dynamically adjusted templates. This parameter change allows the system to maintain fast processing in uniform regions while achieving high accuracy in periodic halftone dot regions.
Solution Approach 2:
The patent makes the interpolation process dynamic by selecting between linear interpolation and pattern matching based on the detected periodicity. This dynamic approach allows the system to process images efficiently using simple linear interpolation where appropriate while employing more sophisticated pattern matching only when needed, thus balancing processing speed and accuracy across different image regions.
Data Source
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AI summary
An image processing apparatus includes a periodicity determining unit configured to determine whether an image region including a target pixel whose pixel value is to be interpolated is a periodic region in which pixel values vary periodically; a first pixel value generating unit configured to generate a pixel value of a pixel using a first interpolation method; a second pixel value generating unit configured to generate a pixel value of a pixel using a second interpolation method different from the first interpolation method; a control unit configured to determine, based on the determination result obtained by the periodicity determining unit, which one of the first and second pixel value generating units is to be used for generating the pixel value of the target pixel; and a pixel value inserting unit configured to insert, to the target pixel, the pixel value generated by one of the first and second pixel value generating units determined by the control unit. The periodicity determining unit includes at least one of: a cycle estimating unit configured to estimate, using pixel values of respective pixels within the image region including the target pixel, a variation cycle of the pixel values; and a partial region periodicity determining unit configured to determine whether each of regions positioned at left and right sides of the target pixel is the periodic region. At least one of the first and second pixel value generating units generates the pixel value of the target pixel using at least one of the variation cycle of the pixel values estimated by the cycle estimating unit and the determination result determined by the partial region periodicity determining unit.