Dual Camera Module Resolving Hyperspectral Resolution Trade-offs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current dual camera modules struggle to enhance the resolution of hyperspectral images and accurately recognize three-dimensional subjects, particularly due to errors caused by camera distance and uneven illumination.
Innovation Solution
A dual camera module system comprising a hyperspectral camera module and an RGB camera module, where the RGB module provides correction values to improve the resolution of hyperspectral images by using red, green, blue, and optionally infrared or ultraviolet light, and the hyperspectral module corrects errors through spectral filtering and image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a hyperspectral camera module is used to capture spectral information, then spectral resolution is improved, but image resolution deteriorates
Solution Approach 1:
The patent combines a hyperspectral camera module and an RGB camera module into a dual-camera system. The RGB camera captures high-resolution spatial information while the hyperspectral camera captures spectral information. The processor integrates data from both cameras, merging their respective strengths to produce images with both high spectral resolution and high spatial resolution.
Solution Approach 2:
The processor acts as an intermediary that receives data from both the hyperspectral camera module and the RGB camera module. It processes and integrates the spectral information from the hyperspectral camera with the high-resolution spatial information from the RGB camera, mediating between the two different data types to produce a unified output image that achieves both spectral and spatial resolution.
2Measurement precision
If multiple camera modules are used to improve image quality, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The processor in the dual camera module performs multiple functions: it processes data from both the hyperspectral and RGB cameras, integrates spectral and spatial information, corrects illumination errors, and generates final output images. This multi-functional approach consolidates the complexity into a single processing unit that handles all tasks, rather than requiring separate processing systems for each camera type.
3Adaptability or versatility
If camera distance is increased to capture broader spectral ranges, then spectral coverage is improved, but measurement accuracy deteriorates
Solution Approach 1:
The system uses feedback from the RGB camera module to correct errors in the hyperspectral image. The RGB camera captures accurate spatial and illumination information that is used to identify and correct errors in the hyperspectral data. This feedback mechanism ensures that even with increased camera distance for broader spectral coverage, the measurement accuracy is maintained through error correction based on the complementary RGB data.
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
The system effectively increases the resolution of hyperspectral images and corrects errors related to camera distance and illumination, enabling accurate recognition of three-dimensional subjects and improved facial recognition.
Implementation Method 1
a hyperspectral filter configured to generate the hyperspectral image
Implementation Method 2
a first image sensor configured to sense the image of the subject
Data Source
AI summary
A dual camera module including a hyperspectral camera module, an apparatus including the same, and a method of operating the apparatus are provided. The dual camera module includes a hyperspectral camera module configured to provide a hyperspectral image of a subject; and an RGB camera module configured to provide an image of the subject, and obtain an RGB correction value applied to correction of the hyperspectral image.