Multi-Channel Camera Registration via White Channel Segmentation
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Solution Overview
Problem
Multi-channel camera systems face challenges in calculating object shifts and distances due to the possibility that image features may not appear in more than one preliminary image, especially with three or more color channels, leading to mis-registration errors and occlusion artifacts.
Innovation Solution
The camera system employs a configuration with a white channel and multiple color channels, where the spectral transmission passbands of the color filters are selected to ensure that the sum of their transmission is constant or minimally overlapping, allowing for accurate calculation of object shifts and distances by compensating for spectral discrepancies and minimizing mis-registration errors, and includes a process for detecting and correcting occlusion artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple color channels (three or more) are used in a multi-channel camera system, then color information and dynamic range are improved, but image features may not appear in more than one preliminary image, leading to mis-registration errors and occlusion artifacts
Solution Approach 1:
The imaging spectrum is segmented into multiple non-overlapping or minimally overlapping passbands for different color channels. This segmentation ensures that each channel captures distinct spectral information while the white channel provides a broadband reference, enabling reliable feature detection across channels for accurate registration.
Solution Approach 2:
A white channel with a broadband passband is introduced as an intermediary between the narrowband color channels. This white channel serves as a mediator that captures features visible across all color channels, providing a reference for registration and reducing mis-registration errors and occlusion artifacts.
2Measurement precision
If color filters with overlapping spectral transmission passbands are used, then color accuracy may be improved, but mis-registration errors increase due to features appearing inconsistently across channels
Solution Approach 1:
The spectral transmission passbands of color filters are designed to be non-overlapping or minimally overlapping, segmenting the spectrum into distinct bands. This segmentation ensures consistent feature appearance across channels while maintaining color accuracy through the white channel reference.
3Illumination intensity
If a white channel with broadband passband is added to the camera system, then signal-to-noise ratio and low-light performance are improved, but device complexity increases
Solution Approach 1:
The white channel with broadband passband serves multiple functions: it provides high signal-to-noise ratio imaging, captures features visible across all color channels for registration reference, and enables luminance calculation. This multi-functionality justifies the added complexity by consolidating several roles into a single channel.
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 configuration improves color accuracy and enables efficient registration of objects across multiple imaging channels, reducing mis-registration errors and occlusion artifacts, resulting in a higher dynamic range and better low-light performance.
Implementation Method 1
the white color filter includes higher light transmission characteristics, for instance including a broader passband and allowing a greater frequency range of light to pass through the filter
Implementation Method 2
The distance between lenses in such cameras can create a parallax effect causing objects to appear at different positions within the images captured by each imaging channel. Calculating the position shifts of such objects between images enables the calculation of distance between objects in a scene.
Data Source
AI summary
An imaging system is configured to identify an object represented by a plurality of preliminary images. The preliminary images are each associated with a different camera imaging channel, and include different image information. An object distance is determined based on the difference in preliminary image information. An object shift is determined based on the object distance and a pre-determined relationship between object shift and object distance. The object shift is applied to the portions of one or more preliminary images representing the object to form shifted preliminary images, and the shifted preliminary images are combined to form a final image.