Compressive-Sensing Image Capture With Optical Mask Filtering
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Solution Overview
Problem
Traditional image sensors produce large amounts of data that are cumbersome and often require unnecessary processing, wasting resources as they reduce data sets mathematically.
Innovation Solution
A compressive-sensing image capture device with an array of sensors and passive or dynamic masks that block electromagnetic radiation, allowing only relevant data to be captured, reducing the need for processing and power consumption by performing filtering in the physical world.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional image sensors capture all electromagnetic radiation, then complete image data is obtained, but large amounts of unnecessary data are produced requiring cumbersome processing
Solution Approach 1:
The patent applies preliminary action by performing the filtering operation in advance during the image capture process itself. The mask array is positioned in the optical path before the sensor array, physically blocking unnecessary electromagnetic radiation from reaching the sensors. This preliminary filtering eliminates the need for subsequent mathematical processing to reduce data, as the data is already in a reduced and useful form when captured.
Solution Approach 2:
The patent extracts only the necessary information from the electromagnetic spectrum by using the mask array to selectively block radiation. Each mask in the array has a specific transmission pattern that allows only certain spatial frequencies or features to pass through to the corresponding sensor. This extraction principle ensures that only relevant data is captured, eliminating unnecessary information before it even reaches the sensor.
2Quantity of substance
If all captured data is processed mathematically to reduce data sets, then manageable data size is achieved, but processing resources are wasted
Solution Approach 1:
The patent replaces the mechanical/computational data reduction system with an optical system. Instead of using mathematical algorithms and processing power to reduce data after capture, the system uses physical masks with specific optical transmission properties to reduce data during capture. This substitution of optical filtering for computational processing dramatically reduces energy consumption while achieving the same data reduction goal.
Solution Approach 2:
The data reduction action is performed preliminarily during the capture phase rather than afterward. The mask array physically encodes the reduction operation into the capture process itself, so that when the sensor reads the data, it is already in the reduced form. This eliminates the need for subsequent mathematical processing and the associated energy consumption.
3Device complexity
If passive masks are integrated into sensors, then device complexity is reduced, but manufacturing precision requirements increase
Solution Approach 1:
The patent merges the mask array with the sensor array into a single integrated unit. The masks are positioned in direct contact with or immediately adjacent to the sensor elements, creating a unified structure where each sensor element has its corresponding mask permanently associated with it. This merging reduces the number of separate components and simplifies the overall device architecture.
Solution Approach 2:
The patent uses copying by creating multiple identical or systematically varied mask patterns that correspond to the sensor array layout. Each mask is a copy or variation of the others, arranged in a regular pattern that matches the sensor grid. This systematic copying approach simplifies manufacturing, as the same mask design can be replicated across the entire array with consistent precision requirements.
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 device captures data that represents coefficients associated with different basis vectors or sampling waveforms, reducing the amount of data processed and saving power and processing capacity while maintaining image quality.
Implementation Method 1
Each sensor in the sensor array has an associated mask that blocks electromagnetic radiation from portions of the sensor
Implementation Method 2
The lenses are condensing lenses that focus the ambient light onto the sensor
Implementation Method 3
The condensing lenses in some embodiments are metalenses that can compensate for small feature size of a pattern mask
Implementation Method 4
A passive mask of some embodiments is a diffractive passive mask that comprises posts of different heights
Data Source
AI summary
Some embodiments provide a novel compressive-sensing image capture device and a method of using data captured by the compressive-sensing image capture device. The novel compressive-sensing image capture device includes an array of sensors for detecting electromagnetic radiation. Each sensor in the sensor array has an associated mask that blocks electromagnetic radiation from portions of the sensor. In some embodiments, an array of passive masks is used to block a particular set of areas of each sensor in the sensor array. In some embodiments, the image capture device also includes an array of lenses corresponding to the sensors of the sensor array such that each sensor receives light that passes through a different lens. Some embodiments of the invention provide a dynamic mask array. In some embodiments, a novel machine trained network is provided that processes image capture data captured by the compressive-sensing image capture device to predict solutions to problems.