3D-LUT Estimation Model for Camera Color Calibration
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Solution Overview
Problem
The difficulty in designing color reproduction using a 3D lookup table (3D-LUT) is high due to the need for extensive parameter setting, which varies across different image sensors and camera models, making it time-consuming to achieve accurate color representation in smartphone cameras.
Innovation Solution
An information processing apparatus and method that generates a color reproduction LUT estimation model to estimate 3D-LUT parameters, using a learning model trained with images of color samples under standard light sources, allowing for easier adaptation of color representation across different camera devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual parameter setting for 3D-LUT is used to achieve accurate color representation, then color accuracy is improved, but the time and effort required for parameter setting increases significantly
Solution Approach 1:
The system performs preliminary characterization of image sensors by capturing images of color samples under controlled lighting conditions and pre-calculating the optimal 3D-LUT parameters. This pre-processing allows the parameters to be stored and automatically applied later, eliminating the need for time-consuming manual parameter setting while maintaining accurate color representation.
Solution Approach 2:
The system enables automatic self-characterization of the image sensor by capturing images of color samples and autonomously generating the appropriate 3D-LUT parameters without requiring manual intervention. The device performs its own color calibration by processing captured images through the learning model and automatically applying the generated parameters, making the entire process self-service oriented.
2Measurement precision
If extensive parameter setting is performed to accommodate variations in image sensors across different models, then color representation accuracy is improved, but the complexity of the design process increases
Solution Approach 1:
The system captures images of color samples under controlled lighting conditions to characterize the specific parameters of each image sensor. By analyzing these captured images, the system automatically determines the optimal 3D-LUT parameters tailored to each sensor's characteristics, accommodating variations across different models without requiring complex manual design processes.
Solution Approach 2:
The system introduces a learning model as an intermediary between the image sensor and the 3D-LUT generation process. This learning model automatically processes captured color sample images and generates appropriate parameters, serving as a mediator that simplifies the design process while maintaining accuracy across different sensor models.
3Measurement precision
If 3D-LUT parameters are customized for each camera model to achieve optimal color reproduction, then color consistency is improved, but the ease of manufacture decreases
Solution Approach 1:
The system enables automatic self-characterization of the image sensor by capturing images of color samples and autonomously generating the appropriate 3D-LUT parameters without requiring manual intervention. The device performs its own color calibration by processing captured images through the learning model and automatically applying the generated parameters, making the entire process self-service oriented.
Solution Approach 2:
The system performs preliminary characterization of image sensors by capturing images of color samples under controlled lighting conditions and pre-calculating the optimal 3D-LUT parameters. This pre-processing allows the parameters to be stored and automatically applied later, eliminating the need for time-consuming manual parameter setting while maintaining accurate color representation.
Data Source
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AI summary
Provided is an information processing apparatus including an acquisition unit that acquires a second image obtained by photographing a color sample by a second camera device and by developing, and an estimation unit that estimates a second 3D-LUT for reproducing, by the first camera device, a color of the color sample in the second image by inputting the second image to a model that has learned a first image obtained by photographing the color sample under a standard light source by a first camera device and by developing as input data and a first 3D lookup table (3D-LUT) used for developing the first image as correct answer data. As a result, the 3D-LUT can be generated more easily.