Camera Lens Emulation via Neural Network Training
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Solution Overview
Problem
Current methods for emulating the imaging characteristics of a camera lens are limited by the need for complex physical modeling and are computationally intensive, making it difficult to achieve accurate emulation of lens-specific looks, especially in real-time applications with interchangeable lenses.
Innovation Solution
A method that configures an emulation process using a training dataset of images captured with both a first and a second camera lens, employing artificial neural networks to determine parameters that replicate the imaging characteristics of the second lens, allowing for the generation of emulated images that mimic the look of the second lens without directly using it.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex physical modeling methods are used to emulate lens imaging characteristics, then the accuracy of lens look emulation is improved, but the computational complexity and processing time increase significantly
Solution Approach 1:
The patent creates a digital copy of the lens's imaging characteristics through captured reference images. Instead of using complex physical models to calculate lens effects, the system captures actual images taken with the target lens under various conditions and stores these as reference data. This digital copy can then be applied to other images through simpler comparison and transformation operations, achieving accurate lens emulation without the computational burden of physical optical modeling.
Solution Approach 2:
The system performs preliminary work by capturing and storing reference images with the target lens before actual emulation is needed. These pre-captured images contain all the lens-specific characteristics (aberrations, bokeh, color rendering) already baked into the pixel data. When emulation is required, the system simply compares the input image against these pre-prepared references and applies the necessary transformations, avoiding the need for complex real-time calculations.
2Measurement precision
If detailed physical parameters of the lens are used for emulation, then the accuracy of imaging characteristics is improved, but the requirement for technical data increases and limits adaptability
Solution Approach 1:
The patent bypasses the need for detailed physical lens parameters by directly copying the visual output of the lens through captured images. Instead of requiring technical specifications like focal length, aperture, or optical formulae, the system simply needs sample images taken with the target lens. This approach makes the system adaptable to any lens regardless of whether its technical data is available, as long as reference images can be captured.
Solution Approach 2:
The patent replaces the mechanical/optical system of physical lens parameters with a data-based system of captured images. Instead of using mathematical models of light propagation through glass elements, the system uses actual pixel data from images taken with the lens. This substitution eliminates the need for detailed technical knowledge of the lens while preserving its visual characteristics.
Data Source
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AI summary
The invention relates to a method for configuring an emulation method for emulating a second camera lens, comprising the steps of: determining a plurality of first images taken using a first camera lens; determining a plurality of second images taken using the second camera lens, the image content of which corresponds to the image content of the plurality of first images; and configuring the emulation method for emulating the second camera lens based on the plurality of first images and the plurality of second images.