Gamma Curve Interpolation for Image Density Stabilization
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Solution Overview
Problem
Conventional image forming technologies using electrophotographic processes struggle to stabilize images due to indirect correction of secondary and tertiary colors, leading to inefficiencies in color adjustment and increased workload, as they primarily correct primary colors and indirectly adjust secondary and tertiary colors, which results in unstable images and lengthy color profiling processes.
Innovation Solution
An image forming apparatus that forms gradation pattern images using n color materials, detects reflectance, and creates gamma curves to correct gradation values for each color, interpolating between primary, secondary, and tertiary colors to generate output image data, allowing for direct and accurate color adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electrophotographic process correction methods are used to adjust primary colors, then primary color accuracy is improved, but secondary and tertiary colors remain unstable due to indirect correction
Solution Approach 1:
The invention segments the color correction process by creating separate gamma curves for primary colors (C, M, Y, K) and secondary/tertiary colors (R, G, B, Pb). This segmentation allows each color type to be corrected independently with dedicated correction data, eliminating the indirect correction problem where secondary and tertiary colors were merely adjusted as byproducts of primary color correction.
Solution Approach 2:
The invention changes the correction parameters by introducing separate gamma curve data for different color compositions. Instead of using a single correction approach for all colors, the system applies specific gamma curve parameters tailored to primary colors and another set for secondary and tertiary colors, enabling precise control over each color type's gradation characteristics.
2Manufacturing precision
If color profiles are generated by measuring thousands of patch images with external devices, then comprehensive color adjustment is achieved, but user workload and time consumption increase significantly
Solution Approach 1:
The invention extracts only the essential correction information needed for color accuracy by measuring a limited set of gradation pattern images rather than thousands of patches. The control section creates gamma curves from this minimal measurement data, eliminating the time-consuming process of measuring and processing extensive color charts while retaining the core correction functionality.
Solution Approach 2:
The image forming apparatus performs self-correction by using its own control section to create gamma curves from measurements taken by its own density detection section. This self-service capability eliminates the need for external color measuring devices and complex user-operated profiling processes, allowing the system to automatically generate correction data from minimal measurements.
3Ease of operation
If linear correction of color compositions is applied as described in prior art, then user workload is reduced, but image stability deteriorates due to inability to handle non-linear gamma correction
Solution Approach 1:
The invention transforms the correction approach from linear to non-linear by implementing gamma curve-based correction. The control section creates gamma curves that capture the non-linear relationship between input and output gradation values, allowing accurate correction of color compositions while maintaining ease of operation through automated processing.
Solution Approach 2:
The system implements feedback by measuring actual gradation values with the density detection section and using these measurements to create accurate gamma curves. The measured reflectance data feeds back into the correction process, enabling the system to adapt to actual printing conditions and maintain image stability through data-driven correction.
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
This approach stabilizes images by directly correcting primary, secondary, and tertiary colors, reducing the workload and time required for color adjustment, and ensures accurate color representation, particularly with cyan, magenta, and yellow toner materials.
Implementation Method 1
a reflectance detection section which detects a reflectance of each of the gradation patches of each of the color patches included in the gradation pattern image formed on the paper
Data Source
AI summary
An image forming apparatus includes a control section extracting a color composition of each color ranging from a first to an nth color from input image data, on the color composition of an mth color, the m being 1 to n−1, performing a first and a second gamma corrections correcting a gradation of the color composition respectively based on a gamma curve for the mth color to obtain a first corrected gradation value, and based on a gamma curve for an (m+1)th color to obtain a second corrected gradation value, and interpolating the first and the second corrected gradation values to determine an output value for the color composition, on the color composition of the nth color, correcting a gradation of the color composition based on a gamma curve for the nth color to obtain an output value for the color composition.