Stereo Camera Spatial Resolution via Mixed Sensor Fusion
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Solution Overview
Problem
Current stereoscopic imaging systems face challenges in achieving high spatial resolution and color fidelity, particularly in occluded areas, due to the limitations of using two full-color cameras or one full-color and one monochrome camera, which can result in reduced image quality and visible color artifacts.
Innovation Solution
The use of a high color density image sensor and a low color density image sensor, where the low color density sensor captures both luminance and color pixels, allowing for the reconstruction of luminance and color values to generate a merged image with improved spatial resolution and color accuracy, using techniques like luminance and chrominance reconstruction and occlusion information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If two full-color cameras are used for stereoscopic imaging, then color fidelity is improved, but spatial resolution is reduced due to color filter array effects and noise increase
Solution Approach 1:
The imaging system is segmented into two separate camera channels: one dedicated to capturing color information (full-color camera) and another dedicated to capturing high-resolution luminance information (monochrome camera). This segmentation allows each camera to optimize for its specific function, with the monochrome camera providing high spatial resolution without color filter array degradation while the full-color camera ensures color fidelity.
2Manufacturing precision
If one full-color camera and one monochrome camera are used, then spatial resolution is improved, but color information is lost in occluded areas
Solution Approach 1:
The system merges the strength of two different imaging approaches by combining a full-color camera and a monochrome camera in a stereoscopic configuration. The full-color camera provides color information for occluded areas while the monochrome camera provides high spatial resolution for visible areas. Image processing algorithms integrate data from both cameras to produce a final image that achieves both high spatial resolution and complete color information.
3Manufacturing precision
If monochrome image sensor is used for reference image, then spatial resolution is improved, but chrominance values are lacking for image registration
Solution Approach 1:
The system uses the full-color camera as an intermediary to provide chrominance information for image registration. While the monochrome camera captures the high-resolution reference image, the full-color camera simultaneously captures color information that serves as a mediator to enable accurate registration. The color data from the full-color camera is used to guide the alignment and integration of images from both cameras, ensuring precise spatial correspondence.
Data Source
AI summary
Techniques are disclosed for capturing stereoscopic images using one or more high color density or “full color” image sensors and one or more low color density or “sparse color” image sensors. Low color density image sensors, may include substantially fewer color pixels than the sensor's total number of pixels, as well as fewer color pixels than the total number of color pixels on the full color image sensor. More particularly, the mostly-monochrome image captured by the low color density image sensor may be used to reduce noise and increase the spatial resolution of an imaging system's output image. In addition, the color pixels present in the low color density image sensor may be used to identify and fill in color pixel values, e.g., for regions occluded in the image captured using the full color image sensor. Optical Image Stabilization and/or split photodiodes may be employed on one or more sensors.