Thin Lens Module Using Neural Network Image Correction
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Solution Overview
Problem
Conventional camera modules with multiple lens elements are too thick due to their high thickness, making them unsuitable for modern mobile devices that are becoming increasingly thinner.
Innovation Solution
A lens module comprising a print circuit board, a spacer with a through hole, a lens assembly, and an image sensor, where the lens assembly captures light and transmits it to the image sensor, and a neural network processes the raw image signals to correct for field curvature and distortion, allowing for a thinner design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple lens elements are used to improve field curvature and distortion correction, then image quality is improved, but module thickness increases
Solution Approach 1:
The patent replaces the traditional mechanical optical correction approach (multiple thick lens elements) with a computational photography approach using neural networks. The neural network processes images captured by a simpler, thinner lens assembly to correct field curvature and distortion digitally, thereby reducing module thickness while maintaining image quality.
Solution Approach 2:
The patent changes the parameter of lens element count from multiple elements to fewer elements, and compensates for the resulting optical imperfections by changing the processing parameter through neural network-based image correction. This parameter transformation allows the system to achieve both thinness and image quality.
2Adaptability or versatility
If lens thickness is reduced to make the module thinner, then adaptability to mobile devices is improved, but optical performance deteriorates
Solution Approach 1:
The patent substitutes mechanical/optical performance improvements (thick lenses) with computational performance improvements (neural network processing). By using AI-based image correction, the system can achieve high optical performance with thinner lenses, thereby improving adaptability to mobile devices without sacrificing image quality.
Solution Approach 2:
The patent introduces a neural network as an intermediary between the thin lens assembly and the final image output. This intermediary processes the raw images to correct optical imperfections, allowing the system to use thin lenses while maintaining high optical performance.
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
The solution enables a thinner lens module that tolerates more field curvature and distortion, enabling high-quality image capture while reducing the overall thickness, suitable for thinner mobile devices.
Implementation Method 1
the image sensor is configured for converting the light into raw image signals
Data Source
AI summary
The present invention discloses a lens module and a system for producing an image. The lens module includes a print circuit board, a spacer, attached onto the print circuit board, and the spacer having a through hole; a lens assembly, supported by the spacer and covered the through hole; an image sensor, mounted on the print circuit board and electrically connected with the print circuit; the lens assembly is configured for capturing light reflected by an object and transmitting the light into the image sensor; the image sensor is configured for converting the light into raw image signals. The lens module may be a simple optics module and thinner than a related lens module.