Multi-spectral Super-pixel Filters Using Binary Logarithmic Cavity Shaping
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Solution Overview
Problem
Current multi-spectral imaging systems are bulky, costly, and limited due to reliance on optics elements for spectral separation, leading to increased cost and complexity, particularly in infrared spectroscopic applications.
Innovation Solution
The development of multi-spectral filter elements with a plurality of sub-filters responsive to different spectral bands, formed using an optical cavity layer with reduced volume through selective removal steps, enabling a denser pixel arrangement and higher resolution by shaping the cavity dimensions suitable for resonation using binary logarithmic function Log2 N steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If optics elements are used to separate spectral information, then spectral filtering capability is achieved, but system size and cost increase
Solution Approach 1:
The filter element is divided into multiple sub-filters within a single integrated structure. Each sub-filter corresponds to a specific spectral band and is formed by selectively removing portions of the optical cavity layer to create cavities with different volumes, enabling multi-spectral filtering without multiple separate optical elements
Solution Approach 2:
Multiple spectral filtering functions are merged into a single filter element. The optical cavity layer serves as a common substrate for all sub-filters, and all sub-filters share the same physical medium (the optical cavity layer), integrating what would traditionally require multiple separate optical components into one unified structure
2Adaptability or versatility
If multiple frames are used to capture multi-spectral data, then spectral information is obtained, but time consumption and system complexity increase
Solution Approach 1:
The filter element is divided into multiple sub-filters within a single integrated structure. Each sub-filter corresponds to a specific spectral band and is formed by selectively removing portions of the optical cavity layer to create cavities with different volumes, enabling multi-spectral filtering without multiple separate optical elements
Solution Approach 2:
A single filter element performs multiple spectral filtering functions simultaneously. The optical cavity layer serves as a common substrate for all sub-filters, enabling the system to capture multiple spectral bands in a single frame rather than requiring multiple sequential frames
3Adaptability or versatility
If scanning architecture is used for one-dimensional imaging, then spectral data is collected, but cost and system complexity increase
Solution Approach 1:
Multiple spectral filtering functions are merged into a single filter element. The optical cavity layer serves as a common substrate for all sub-filters, and all sub-filters share the same physical medium (the optical cavity layer), integrating what would traditionally require multiple separate optical components into one unified structure
Solution Approach 2:
The patent transitions from one-dimensional scanning architecture to two-dimensional array architecture. By arranging multiple sub-filters in a spatial array within each filter element, the system can capture spectral information across a two-dimensional field of view simultaneously, eliminating the need for mechanical scanning
4Adaptability or versatility
If optical cavity volume is reduced in multiple spatial regions, then multi-spectral filtering is enabled, but manufacturing complexity increases
Solution Approach 1:
The optical cavity layer is formed as a complete, uniform layer before any selective removal. This preliminary formation of the full cavity layer simplifies manufacturing by establishing a consistent baseline structure that can then be selectively modified. The selective removal process builds upon this pre-formed layer rather than attempting to create different cavity volumes from scratch
Solution Approach 2:
The optical cavity layer has different volumes in different spatial regions, with each region's cavity volume tailored to the specific spectral filtering requirements of that region. This local variation in cavity volume enables each sub-filter to be optimized for its designated spectral band while maintaining a unified manufacturing process
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 results in low-cost, compact multi-spectral sensors capable of spatially filtering multiple spectral regions with improved device performance, mitigating diffraction and enabling higher resolution through a denser pixel arrangement and discretely tuned optical filters.
Implementation Method 1
shaping the cavity dimensions suitable for resonation using binary logarithmic function Log2 N steps
Data Source
AI summary
Multi-spectral filter elements and methods of formation are disclosed. Each multi-spectral filter element may include a plurality of sub-filters that are, in some examples, each adapted to respond to electromagnetic radiation within respective ones of a plurality of spectral bands. A method example includes forming an optical cavity layer. Volume of the optical cavity layer can be reduced in at least N−1 number of spatial regions. The reducing may include a number of selective removal steps equal to the binary logarithm function Log2 N. In this example, each spatial region corresponds to a respective one of the plurality sub-filters. The plurality of sub-filters includes at least N sub-filters. In particular examples, the respective ones of the plurality of spectral bands may be at least partially discrete with respect to each other.