High Spatial Temporal Resolution Image Data Generation
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Solution Overview
Problem
Conventional image capturing technologies face challenges in achieving high spatial and temporal resolutions without increasing camera complexity or reducing optical efficiency, particularly in capturing RGB color images, which often result in decreased image quality due to light splitting and color filter usage.
Innovation Solution
A system that splits incoming light into wavelength ranges, capturing high spatial resolution images in one range and low spatial resolution images with high temporal resolution in others, then converts the temporal resolution of the former to match the latter using correspondence between images, allowing for high spatial and temporal resolution RGB images without compromising optical efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light is split into multiple wavelength ranges with color filters to capture RGB images, then color image quality is improved, but optical efficiency decreases and image quality deteriorates
Solution Approach 1:
The patent segments the imaging process into two independent channels: a first imaging sensor captures luminance information (Y) without color filters for high optical efficiency, while a second imaging sensor captures chrominance information (Cb, Cr) through color filter arrays. This segmentation allows each sensor to optimize for its specific function, resolving the contradiction between color image quality and optical efficiency.
Solution Approach 2:
The patent introduces an intermediary processing unit that combines the luminance signal from the first sensor with the chrominance signals from the second sensor to reconstruct the final RGB image. This intermediary synthesis allows the system to achieve high color quality through computational processing rather than relying solely on optical filtering, thereby maintaining optical efficiency.
2Measurement precision
If high spatial resolution imaging is used to capture detailed images, then image detail is improved, but data transfer rate increases and device complexity increases
Solution Approach 1:
The patent applies different resolution characteristics to different image components: the luminance channel uses high spatial resolution for detailed brightness information, while the chrominance channel uses lower resolution since human vision is less sensitive to color details at high resolutions. This local quality differentiation reduces overall data volume and processing complexity while maintaining perceived image quality.
Solution Approach 2:
The patent changes the resolution parameters differently for different imaging channels and allows temporal resolution to vary between frames. By dynamically adjusting resolution parameters based on image content and processing requirements, the system maintains high spatial resolution where needed while reducing data handling complexity in other areas.
3Measurement precision
If frame rate is increased to improve temporal resolution, then motion tracking is improved, but data transfer rate increases
Solution Approach 1:
The patent applies partial action by capturing chrominance information at lower temporal resolution than luminance information. The first sensor captures high-frame-rate luminance data for smooth motion, while the second sensor captures chrominance data at reduced frame rates since color information changes more slowly. This partial application of high temporal resolution only where most critical reduces overall data transfer requirements.
Solution Approach 2:
The patent uses periodic action through motion compensation techniques where the system predicts and fills in missing chrominance frames based on temporal patterns. By periodically sampling chrominance information at lower rates and using predictive algorithms to interpolate missing data, the system achieves high temporal resolution for motion tracking while maintaining lower data transfer rates.
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
Enables the acquisition of high-resolution image data at reduced data transfer rates, maintaining image quality and portability without increasing camera size or complexity, effectively addressing the limitations of prior art.
Implementation Method 1
a light splitting section for splitting incoming light that has come from a subject into a number of wavelength ranges
Implementation Method 2
a first image capturing section which receives a portion of the split light that falls within a wavelength range with the highest luminosity factor, thereby getting a first image
Implementation Method 3
a resolution converting section for converting the temporal resolution of the first image into that of the second image using the first and second images
Data Source
AI summary
The shooting, recording and playback system 100 of the present invention receives incoming light 101, stores an image shot, and then subjects the image shot to be reproduced to resolution raising processing, thereby outputting RGB images with high spatial resolution and high temporal resolution (ROUT GOUT BOUT) 102. The system 100 includes a shooting section 103, a color separating section 104, an R imaging sensor section 105, a G imaging sensor section 106, a B imaging sensor section 107, an image shot storage section 108, an image shot writing section 109, a memory section 110, an image shot reading section 111, a spatial resolution upconverter section 112, a temporal resolution upconverter section 113, an output section 114, and a line recognition signal generating section 185. The system can get image data with high spatial resolution and high temporal resolution without getting the camera configuration complicated and without decreasing the optical efficiency.