Optical-Digital Image Stitching for High-Resolution Wide-Angle Capture
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Solution Overview
Problem
Existing image capture methods face challenges when trying to zoom in on wide-angle images due to pixilation from interpolation, or when zooming out from high magnification images, as they often miss capturing details in outlying regions of three-dimensional real space.
Innovation Solution
A method that captures first image data at a high magnification index and second image data at a lower magnification index, digitally zooms the second image data to match the first, and stitches them together to create a seamless image at the desired magnification index.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide-angle view is captured at low optical magnification to capture more three-dimensional real space, then the field of view is improved, but image quality deteriorates when zooming in due to pixilation
Solution Approach 1:
The image is divided into multiple regions, each captured at different magnification levels. The system segments the capture process into high-magnification regions (captured optically zoomed) and low-magnification regions (captured wide-angle), then stitches them together. This allows different parts of the image to have appropriate quality for their intended use.
Solution Approach 2:
The patent introduces a new dimension to image capture by combining optical zoom capabilities with digital stitching. Instead of a single magnification level, the system creates a multi-dimensional image space where different regions exist at different magnification levels, effectively adding a magnification dimension to the traditional two-dimensional image plane.
2Length of moving object
If digital zoom is used to magnify a portion of the still image, then the magnification is achieved, but image quality deteriorates due to interpolation and pixilation
Solution Approach 1:
The system performs preliminary optical zoom capture of specific regions at high magnification before the final image assembly. By pre-capturing the zoomed regions optically (rather than digitally interpolating later), the high-quality image data is already available in advance, eliminating the need for quality-degrading digital zoom interpolation.
Solution Approach 2:
The patent creates a copy of the scene at different magnification levels. Instead of digitally scaling up a single low-resolution image, the system captures multiple copies of relevant scene portions at the desired high magnification using optical zoom, then integrates them into the final composite image.
3Manufacturing precision
If a still image is captured at high magnification index, then image quality is improved, but the field of view deteriorates due to lack of outlying regions
Solution Approach 1:
The system merges multiple images captured at different magnification levels into a single composite image. High-magnification images (captured with optical zoom) are combined with wide-angle images (captured at low magnification), creating a unified image that contains both detailed close-up regions and broad contextual regions.
Solution Approach 2:
Different regions of the final image are assigned different quality characteristics based on their intended use. Regions requiring detail (captured with optical zoom) have high local quality, while regions providing context (captured wide-angle) have lower local quality but broader coverage. Each region's quality is optimized for its specific function.
Data Source
AI summary
A method for generating images. The method includes capturing first image data representing a first scene taken optically at a first magnification index, wherein the first image data comprises a first region of an image. The method includes capturing second image data representing a second scene taken optically at a second magnification index that is less than the first magnification index, wherein the second image data comprises a second region of the image. The method includes digitally zooming the second image data in the second region to the first magnification index. The method includes digitally stitching the second image data in the second region to the first image data in the first region.