Stereo Imaging With Selective Extended Depth-of-Field Correction
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Solution Overview
Problem
Existing image processing techniques fail to effectively correct visual artifacts such as blur and noise, particularly in extended-reality environments, leading to reduced immersiveness and increased computational burden, and are not feasible for stereo imaging systems due to economic and heuristic constraints.
Innovation Solution
An imaging system with two cameras, one for each eye, applies selective extended depth-of-field correction to one image while performing defocus blur correction, image sharpening, or contrast enhancement on the other, using customized neural networks for different focusing distance ranges, reducing computational load and enhancing visual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If learning-based methods are used to extend depth of field, then depth of field can be extended, but computational processing becomes heavier and image contrast deteriorates
Solution Approach 1:
The patent divides the stereo image pair into two separate images and applies different correction methods to each. One image receives full EDOF correction while the other receives lighter processing (defocus blur correction, sharpening, or contrast enhancement), segmenting the computational workload to reduce overall processing load while maintaining visual quality.
Solution Approach 2:
The patent applies different processing qualities to different images based on their role in the stereo pair. By applying the more computationally intensive EDOF correction to only one image and lighter corrections to the other, the system optimizes computational resources while maintaining adequate quality for both eyes.
2Reliability
If traditional algorithms with constraints are used to resolve visual artifacts, then artifact correction can be achieved, but heuristic parameter-tuning and expensive computation are required
Solution Approach 1:
The patent applies partial correction to one image and full correction to the other. By applying defocus blur correction, sharpening, or contrast enhancement to one image instead of full EDOF correction, the system achieves adequate artifact reduction with lower computational cost, while the other image receives complete correction to ensure overall visual quality.
3Manufacturing precision
If EDOF correction is applied to both images in a stereo system, then visual quality can be maximized, but the implementation becomes economically unfeasible
Solution Approach 1:
The patent merges different correction approaches for the two images in a stereo pair. By combining EDOF correction for one image with lighter corrections (sharpening, contrast enhancement, defocus blur correction) for the other, the system achieves acceptable visual quality for both eyes while reducing the overall computational burden to economically feasible levels.
Data Source
AI summary
An imaging system including a first camera and a second camera corresponding to a first eye and a second eye of a user, respectively; and at least one processor. The at least one processor is configured to control the first camera and the second camera to capture a sequence of first images and a sequence of second images of a real-world environment, respectively; and apply a first extended depth-of-field correction to one of a given first image and a given second image, whilst applying at least one of: defocus blur correction, image sharpening, contrast enhancement, edge enhancement to another of the given first image and the given second image.