Image Layout Size Calculation for Blurriness Control
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Solution Overview
Problem
Images that are too large for expected output sizes can become blurred during printing or display, leading to undesirable visual quality.
Innovation Solution
An image layout size calculation apparatus that determines a blurriness value for image areas and calculates a layout size to ensure the output image has a blurriness value equal to or smaller than a threshold, using the number of pixels and resolution of the output device, while optionally emphasizing sharpness and maintaining the relationship between main subject and background blurriness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If an original image is used for output, then the image data is preserved, but the output image becomes blurred when the original image is too large compared to the expected output size
Solution Approach 1:
The system performs preliminary analysis of the original image to detect blurriness and calculate the appropriate layout size before output. By determining the maximum layout size that maintains acceptable blurriness levels in advance, the system prevents blurriness from occurring during the output process rather than attempting to correct it afterward.
Solution Approach 2:
The system changes the layout size parameter based on the detected blurriness level of the original image. By dynamically adjusting the layout size to ensure that the blurriness value in the output image remains below a predetermined threshold, the system optimizes output quality while preventing excessive blurriness.
2Loss of information
If the layout size is increased to maintain image detail, then the number of pixels is preserved, but the blurriness increases when the output size is limited
Solution Approach 1:
The system dynamically adjusts the layout size parameter based on the relationship between the number of pixels and the detected blurriness. By calculating the maximum layout size that keeps blurriness below the threshold while utilizing the available pixel count, the system optimizes the balance between preserving image detail and preventing blurriness.
Solution Approach 2:
The system replaces manual judgment of image quality with automated blurriness detection and layout size calculation. By using computational algorithms to detect blurriness and determine optimal layout sizes, the system objectively balances image detail preservation with blurriness prevention.
3Manufacturing precision
If blurriness detection and layout size calculation are performed, then output image quality is improved, but the processing time increases
Solution Approach 1:
The system performs blurriness detection and layout size calculation as preliminary steps before the actual image output process. By completing these quality control calculations in advance, the system ensures that subsequent output operations can proceed efficiently without requiring iterative adjustments or post-processing corrections.
Solution Approach 2:
The system automatically performs blurriness detection and layout size determination without requiring manual intervention. By making the quality control process self-service and automated, the system minimizes the time burden on users while maintaining high output image quality through systematic blurriness management.
Data Source
AI summary
Provided are an image enlargement/reduction rate calculation apparatus, an image enlargement/reduction rate calculation method, and an image enlargement/reduction rate calculation program which are capable of outputting an image with a small blurriness degree. A blurriness value is calculated for each image area, and the smallest blurriness value is decided (step S24). Resolution of a printer that prints the image is read (step S25). An enlargement/reduction rate in which the blurriness value is equal to or smaller than a second threshold value is calculated based on the decided blurriness value (step S26).