Multi-Channel Optics Image Interpolation Grid
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Solution Overview
Problem
Multi-channel imaging systems face challenges in achieving sufficient resolution and image quality due to optical distortions and high manufacturing tolerances required for precise alignment of microlens arrays and image sensors, leading to artifacts in the overall image, especially in applications like mobile phones and cameras.
Innovation Solution
An image recording device with a large pixel image sensor and multi-channel optics that assigns imaging values to each pixel based on its imaging direction or lateral position, using an interpolator to standardize the distribution of scanning values across a regular grid, thereby avoiding transition problems between sub-areas and compensating for distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If multi-channel optics with microlens arrays are used to reduce camera module size, then the structural height along the optical axis is reduced and depth of focus is increased, but optical distortions occur in each channel making it difficult to join individual partial images
Solution Approach 1:
The patent divides the image sensor into multiple sub-areas, each associated with a microlens array channel. This segmentation allows each channel to be processed independently with its own distortion characteristics, enabling the use of smaller microlenses with shorter focal lengths while maintaining overall system functionality. The segmentation resolves the contradiction by allowing independent optimization of each channel rather than requiring perfect alignment across the entire system.
Solution Approach 2:
The patent changes the approach from physical alignment precision to digital parameter transformation. By capturing distortion characteristics for each pixel and applying per-pixel transformation parameters during image processing, the system compensates for optical distortions without requiring high manufacturing precision. This parameter-based approach resolves the contradiction between reduced structural height and maintained alignment precision.
2Manufacturing precision
If microlens arrays and image sensor sub-areas are aligned with high precision to minimize assembly tolerances, then manufacturing costs and complexity increase, but image quality and resolution improve
Solution Approach 1:
The patent replaces the mechanical alignment system with a digital processing system. Instead of relying on precise physical alignment of microlens arrays with image sensor sub-areas, the system uses software-based distortion compensation and image stitching algorithms. This substitution resolves the contradiction by trading mechanical precision requirements for computational processing, significantly easing manufacturing and assembly while maintaining image quality.
Solution Approach 2:
The patent introduces an intermediary processing layer between the optical capture stage and the final image output. This intermediary layer includes distortion characteristic capture, transformation parameter calculation, and per-pixel image processing. This intermediary resolves the contradiction by decoupling the optical hardware requirements from the final image quality, allowing simpler manufacturing while maintaining high image quality through digital mediation.
3Area of stationary object
If individual partial images from multiple channels are joined to form an overall image, then the overall field of view is increased, but artifacts appear in the overall image especially along overlapping areas of partial images
Solution Approach 1:
The patent performs preliminary capture of distortion characteristics for each pixel during a calibration phase before actual image capture. These pre-captured distortion parameters are stored and applied during normal operation. This preliminary action resolves the contradiction by preparing the correction data in advance, enabling seamless stitching of multiple channels without artifacts during actual imaging.
Solution Approach 2:
The patent implements a feedback mechanism where distortion characteristics are captured and measured, then used to calculate transformation parameters that are applied to correct the images. The system continuously refines the distortion model based on captured data, creating a closed-loop feedback system. This feedback resolves the contradiction by using actual measured distortion data to optimize the stitching process, eliminating artifacts while maintaining expanded field of view.
Data Source
AI summary
The invention relates to obtaining an improved relationship between hardware and manufacturing effort, and image quality, by using a multichannel optic, wherein the sampled values of the pixels are disposed according to a display direction from which the optic displays objects at each pixel, or according to a lateral display position in a focal depth plane displayed by the optic at each pixel, and the distribution of sampled values of the pixels so distributed are interpolated at intersection points of a regular grid extending over the entire distribution of sampled values. Processing is made uniform over the entire image in said manner, so that transition problems between the partial regions are avoided.