Lensless Optical Sensing via Odd-Symmetry Grating Diffraction
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Solution Overview
Problem
Conventional cameras face challenges in miniaturization and cost reduction while maintaining image quality, as they rely on traditional lens-based systems that are difficult to miniaturize and cost-effectively scale down.
Innovation Solution
The development of lensless imaging architectures using odd-symmetry gratings and photodetector arrays, which utilize diffraction gratings to project near-field spatial modulations onto the photodetector array, allowing for the creation of smaller, more cost-effective imaging devices by leveraging computational imaging techniques to correct optical aberrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional lens-based camera systems are used, then image quality can be maintained, but device size and manufacturing cost increase
Solution Approach 1:
The patent removes the lens component entirely from the imaging system, extracting only the essential light-modulating function and replacing it with a diffractive optical element directly integrated with the sensor array. This elimination of the lens enables ultra-miniaturization while maintaining imaging capability through computational reconstruction of images from the diffractive patterns captured by the sensor.
Solution Approach 2:
The patent merges the diffractive optical element and the sensor array into a single integrated structure, where the diffractive element is positioned in direct contact with or immediately adjacent to the sensor. This integration eliminates the need for separate lens mounting, alignment mechanisms, and air gaps, dramatically reducing device volume and enabling the ultra-miniature form factor.
2Measurement precision
If traditional lens-based camera systems are used, then image quality can be maintained, but manufacturing cost increases
Solution Approach 1:
The patent replaces expensive, precision-manufactured lenses with diffractive optical elements that can be fabricated using standard semiconductor photolithography processes. These diffractive structures are essentially patterned surfaces that can be mass-produced at low cost using existing CMOS fabrication infrastructure, eliminating the need for costly optical grinding, polishing, and coating operations required for traditional lenses.
Solution Approach 2:
The patent substitutes mechanical optical components (lenses requiring precise mechanical mounting and alignment) with planar diffractive structures that are lithographically defined. This replacement eliminates complex mechanical assemblies, reduces the number of manufacturing steps, and enables direct integration with standard semiconductor fabrication processes, significantly lowering manufacturing cost.
3Volume of moving object
If diffractive optical elements are used instead of lenses, then device size and cost are reduced, but optical aberrations are introduced
Solution Approach 1:
The patent converts the typically harmful optical aberrations introduced by diffractive elements into useful information. By deliberately designing the diffractive structure to produce specific, known aberration patterns, the system captures these aberrated images and uses computational algorithms to reverse the aberrations during image reconstruction. This approach transforms what would be unwanted optical defects into a controlled intermediate step that enables both miniaturization and high-quality image recovery.
Solution Approach 2:
The patent changes the operational parameters of the imaging system by operating in the computational domain rather than relying solely on optical perfection. By capturing raw diffractive patterns and applying digital signal processing, deconvolution, and iterative reconstruction algorithms, the system compensates for optical imperfections through parameter adjustments in the computational realm, achieving high image quality despite simplified optics.
4Volume of moving object
If lensless imaging architecture is used, then device size is reduced, but depth information extraction becomes more challenging
Solution Approach 1:
The patent incorporates depth-coding features directly into the diffractive optical element design, such as varying the diffractive pattern across different regions of the element or using multiple diffractive layers with different focal properties. This preliminary encoding of depth information in the optical domain simplifies subsequent computational extraction, as the depth data is already embedded in the captured diffractive patterns rather than requiring complex post-capture analysis.
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
This approach enables the construction of ultra-miniature cameras that are significantly smaller and less expensive than traditional lens-based systems, while maintaining or improving image resolution and depth information extraction through computational means.
Implementation Method 1
a diffractive optical element and a sensor array, the diffractive optical element having a known response to light from different directions and/or different ranges
Implementation Method 2
the sensor array captures a diffraction pattern of the light
Data Source
Figure 1A~1B
Figure 2~3
Figure 4A~4B
AI summary
A sensing device with an odd-symmetry grating projects near-field spatial modulations onto an array of closely spaced pixels. Due to physical properties of the grating, the spatial modulations are in focus for a range of wavelengths and spacings. The spatial modulations are captured by the array, and photographs and other image information can be extracted from the resultant data. Pixels responsive to infrared light can be used to make thermal imaging devices and other types of thermal sensors. Some sensors are well adapted for tracking eye movements, and others for imaging barcodes and like binary images. In the latter case, the known binary property of the expected images can be used to simplify the process of extracting image data.