One Point Color Image Generation Using Composite Luminance
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Solution Overview
Problem
Conventional methods for generating one point color images rely solely on color images, which limits the fidelity of luminance information, whereas using a monochrome image can provide higher quality luminance reproduction, but existing technologies do not effectively combine these for high-quality one point color image generation.
Innovation Solution
An image processing apparatus and method that generates a composite image by combining a color image and a monochrome image captured from different viewpoints, allowing only a partial area of the image to be colored with pixel values from the composite image and the remaining area to use pixel values from the monochrome image, with user or automatic selection of the colorization area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only a color image is used to generate a one point color image, then the process is simple, but the luminance information fidelity is insufficient
Solution Approach 1:
The patent combines a color image and a monochrome image through composition processing to generate a composite image. The color image provides color information while the monochrome image provides high-fidelity luminance information. By merging these two images, the system achieves both color representation and accurate luminance reproduction in the final one point color image.
Solution Approach 2:
The patent creates a composite image that functions as a composite material, combining the properties of two different image types. The composite image contains both color data from the color image and superior luminance data from the monochrome image, resulting in a hybrid image product that leverages the strengths of both source images.
2Manufacturing precision
If a composite image is generated using both color and monochrome images, then image quality improves, but processing complexity increases
Solution Approach 1:
The patent divides the final image into two distinct regions: a colorization area that uses the composite image and a non-colorization area that uses only the monochrome image. This segmentation allows selective application of processing techniques, improving image quality in the colorized region while managing overall processing complexity through regional differentiation.
Solution Approach 2:
The patent applies different image processing strategies to different regions of the image. The colorization area receives the enhanced composite image with both color and high-fidelity luminance, while the non-colorization area uses the simpler monochrome image processing. This local quality approach optimizes image quality where needed while controlling processing complexity elsewhere.
3Ease of operation
If the colorization area is manually specified, then user control is high, but operation time increases
Solution Approach 1:
The patent performs composition processing between the color image and monochrome image in advance, before the final output is generated. This preliminary action creates the composite image that can be quickly applied to the colorization area, reducing the time required during actual operation while maintaining user control over area selection.
Data Source
AI summary
An apparatus and a method for generating a high-quality one point color image are provided. A composite image generation unit that generates a composite image by executing composition processing using a color image and a monochrome image captured from different viewpoints, and an output image generation unit that generates a one point color image in which only a partial area of the image is colored are included. The output image generation unit generates a one point color image in which a colorization area in the one point color image is set as an area to which pixel values of the composite image are output, and a non-colorization area is set as an area to which pixel values of the monochrome image are output. The colorization area is selected by either user selection or automatic selection. For example, user-specified area information, subject distance information, and the like are used for the execution.