Lensless Imaging Resolution Enhancement via Point Spread Function
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Solution Overview
Problem
Conventional digital imaging devices face challenges in increasing resolution and focus without adding costly or complex components, as they often require significant computational resources and multiple expensive sensors, and are limited by physical constraints.
Innovation Solution
A lensless imaging system that uses a processor to determine and utilize point spread functions for enhancing image resolution and focus, employing compressive measurement techniques and shutter arrays or micro mirror arrays to generate images beyond physical limitations, allowing for selected resolution and focus adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional components are added to increase resolution, then image resolution is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the traditional mechanical/optical lens-based imaging system with a computational approach. Instead of using physical lenses and multiple sensors to achieve high resolution, the system uses a single sensor array combined with computational algorithms (including point spread function analysis and super-resolution techniques) to reconstruct high-resolution images from multiple low-resolution measurements. This substitution of mechanical components with computational processing directly resolves the contradiction between improving resolution and reducing device complexity.
2Measurement precision
If multiple expensive sensors are used to improve resolution, then image resolution is improved, but device cost increases
Solution Approach 1:
The patent segments the imaging process into multiple temporal phases where a single sensor array captures multiple low-resolution images at different time points or with different optical conditions. By dividing the imaging task across time and computational processing rather than using multiple simultaneous sensors, the system achieves high resolution equivalent to multiple sensors while using only one sensor array, thereby reducing cost.
Solution Approach 2:
The system creates multiple virtual copies of the imaging process through computational reconstruction. Instead of physically duplicating sensors, the patent uses algorithms to generate multiple high-resolution image versions from single sensor measurements, effectively copying the information-gathering capability without the associated hardware cost.
3Measurement precision
If computational capabilities are increased to enhance image processing, then image quality is improved, but processing requirements and complexity increase
Solution Approach 1:
The patent performs preliminary computational actions by pre-calculating and storing point spread functions and other calibration data before actual imaging. This pre-processing allows the main image reconstruction algorithms to work more efficiently during real-time or near-real-time imaging, reducing the computational burden during critical imaging operations while still achieving high image quality.
Data Source
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AI summary
An exemplary system includes at least one detector configured to provide an output based on a detected input. A plurality of input control elements control the input detected by the detector. A processor is configured to determine at least one point spread function based on a condition of the detector, a condition of the input control elements and a selected distance associated with the output. The controller is configured to generate data based on the output and the at least one point spread function, the generated data having at least one aspect.