Gamma Correction Table Generation Using Density Patches
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Solution Overview
Problem
Conventional methods for generating gamma correction tables struggle to obtain precise output density characteristics due to low resolution sensors and the difficulty in relating measured output densities to input tone values, especially for contour and fine line portions in image forming devices.
Innovation Solution
The method involves creating a gamma correction table by obtaining and correcting density information from a sensor using density patches that include overlapping cells with separated dots, allowing for precise measurement and correction of output density characteristics, particularly for fine lines and plane portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a sensor with low resolution is used to measure output density in contour portions, then the measurement process is simpler and faster, but the measurement precision deteriorates because multiple input tone values appear in a mixed state around the pixel of interest
Solution Approach 1:
The patent divides the measurement process into two distinct segments: one for contour portions using a first gamma correction table, and another for non-contour portions using a second gamma correction table. This segmentation allows each measurement approach to be optimized for its specific use case, resolving the contradiction between measurement speed and precision by applying the appropriate method to the appropriate region.
Solution Approach 2:
The patent applies different measurement and correction strategies to different regions of the image based on their local characteristics. Contour portions receive dedicated attention with specific gamma correction processing, while non-contour portions use standard measurement approaches. This local quality approach ensures that each region is measured and corrected with the appropriate level of precision and speed.
2Manufacturing precision
If multiple gamma correction tables are generated for different areas (contour and non-contour portions), then the manufacturing precision of the correction process is improved, but the device complexity increases
Solution Approach 1:
The patent segments the image processing into distinct regions (contour and non-contour portions) and applies different gamma correction tables to each segment. This segmentation enables precise correction for each region type while maintaining manageable system complexity through clear separation of correction strategies.
Solution Approach 2:
Different gamma correction tables are applied to different local regions of the image based on their characteristics. Contour portions use one correction table optimized for edge detection and line quality, while non-contour portions use another table optimized for general tone reproduction. This local quality approach improves overall correction precision without requiring a single overly complex correction system.
3Adaptability or versatility
If screen processing is applied to convert input digital image data into quasi-tone image data, then the adaptability to the image forming device is improved, but the measurement precision of output density deteriorates due to resolution loss
Solution Approach 1:
The patent performs preliminary detection of contour portions in the input image data before applying screen processing. This preliminary action allows the system to identify regions that require special handling and apply appropriate gamma correction strategies, thereby preserving measurement precision even after screen processing converts the image to quasi-tone representation.
Solution Approach 2:
The patent applies different processing strategies to different regions: contour portions are detected and handled with specific gamma correction to preserve edge sharpness and line quality, while non-contour portions undergo standard screen processing for tone conversion. This local quality approach maintains adaptability to the image forming device while minimizing measurement precision loss in critical regions.
Data Source
AI summary
A gamma correction table generation method includes: obtaining density information by reading, with a reading sensor, a density patch output by an image forming device in a range wider than a cell, the density patch including a plurality of cells disposed such that a part of the cells as a unit representing a tone overlaps with each other and dots included in each of the cells are separated from each other to an extent that no influence is exerted on each other on a recording medium which the image forming device outputs; correcting the density information according to a number of the cells in the density patch; and generating a gamma correction table based on the corrected density information.