Image Edge Sharpening for Dimensional Reduction
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Solution Overview
Problem
Existing image processing methods, such as the bi-linear and bi-cubic methods, tend to degrade the sharpness of image edges during dimensional reduction, especially when the reduction ratio is high, leading to unnatural or unclear edges in dimensionally reduced images.
Innovation Solution
An image processing method that adjusts the sharpening filter based on the reduction ratio to amplify pixel density changes at edges, using correction data modified according to the reduction ratio, ensuring appropriate edge emphasis regardless of the reduction ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pixel values are averaged using bi-linear, bi-cubic, or average pixel method for dimensional reduction, then image quality is improved and jaggies are suppressed, but sharpness of edges is degraded
Solution Approach 1:
The patent applies edge emphasizing processing after dimensional reduction to compensate for the sharpness degradation caused by averaging methods. By performing the sharpening operation as a subsequent corrective action, the system maintains both the quality benefits of averaging and restores edge sharpness.
Solution Approach 2:
The patent modifies pixel density values through edge emphasizing processing that amplifies changes at edges. This parameter change approach adjusts the density values to enhance edge visibility while preserving the overall image quality achieved through averaging methods.
2Measurement precision
If edge emphasizing process is applied to boosted amplify changes in density values at edges, then sharpness is improved, but edges may be over-emphasized or under-emphasized depending on reduction ratio
Solution Approach 1:
The patent dynamically adjusts the edge emphasizing parameters based on the reduction ratio. The correction data is modified according to the specific reduction ratio applied, allowing the system to adapt the sharpening strength to match the degree of dimensional reduction and achieve consistent edge sharpness across different reduction scenarios.
Solution Approach 2:
The patent changes the parameters of the edge emphasizing filter based on the reduction ratio. By modifying the correction data parameters according to the reduction ratio, the system achieves adaptability to various reduction levels while maintaining appropriate edge emphasis.
3Ease of manufacture
If fixed sharpening filter is used for dimensional reduction, then processing is simple, but edge emphasis does not match various reduction ratios
Solution Approach 1:
The patent modifies the parameters of the sharpening filter based on the reduction ratio. By changing the correction data parameters according to the reduction ratio, the system achieves adaptability to various reduction levels while maintaining appropriate edge emphasis, resolving the contradiction between fixed filter simplicity and ratio-specific accuracy.
Data Source
AI summary
A method for processing an image includes: determining a reduction ratio that falls within a predetermined range; generating reduced image data indicative of a reduced image based on original image data indicative of an original image by dimensionally reducing the size of the original image to the size of the reduced image by the determined reduction ratio, the reduced image data indicating density values of pixels contained in the reduced image; and emphasizing edges in the reduced image by amplifying a change in the density values of pixels belonging to the edges in the reduced image based on the density values of the pixels contained in the reduced image. The emphasizing edges includes: correcting the density values of the pixels in the reduced image data by using correction data; and modifying the correction data to be used for correction of the density values of the pixels in the reduced image data, the correction data being modified dependently on the reduction ratio, to thereby vary a level of amplification of the change in the density values dependently on the reduction ratio.