Active Optical Compressive Sensing With Pseudorandom Mask Encoding
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Solution Overview
Problem
Existing imaging systems require significant power and storage resources due to the linear scaling of signal-to-noise ratio and data collection with scene size, inefficiently using power and memory before compressing signal data.
Innovation Solution
Measure and store signal data from illuminated scenes in a compressed form using pseudorandom masks, reducing measurements and storage requirements by employing a convex optimization algorithm to recover images or signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging systems measure and store full-resolution signal data from illuminated scenes, then image quality and signal-to-noise ratio are maintained, but power consumption and storage requirements scale linearly with scene size
Solution Approach 1:
The patent extracts only the essential signal information needed for image reconstruction by using compressed sensing measurements. Instead of capturing and storing all pixel data, the system takes out only the critical measurements (fewer than full resolution) that contain sufficient information to recover the image, thereby reducing power consumption and storage requirements while maintaining signal-to-noise ratio.
Solution Approach 2:
The patent changes the measurement parameter from full-resolution pixel values to compressed sensing measurements. By transforming the data representation from spatial domain (full image pixels) to a compressed measurement domain using pseudorandom masks, the system achieves equivalent image quality with significantly reduced data volume, lowering both power consumption and storage needs.
2Loss of information
If conventional imaging systems collect and store complete signal data for every pixel, then full image detail is preserved, but storage requirements scale linearly with scene size
Solution Approach 1:
The patent extracts only the essential information needed to reconstruct the image by taking compressed measurements rather than storing all pixel data. The pseudorandom mask sequences extract critical signal components that contain sufficient information for image recovery, eliminating the need to store redundant data while preserving image detail.
Solution Approach 2:
The patent creates a compressed copy of the image data through mathematical transformation rather than storing the original full-resolution data. The compressed sensing measurements serve as a compact representation that can be transformed back into the full image, providing an efficient copy that uses minimal storage space while preserving all necessary image information.
3Productivity
If imaging systems use pseudorandom masks to encode optical signals before detection, then the number of measurements is reduced, but system complexity increases
Solution Approach 1:
The patent introduces pseudorandom masks as an intermediary element between the optical signal and the detector. These masks encode the optical signal into a compressed form that can be measured efficiently. The masks act as a mediator that transforms the measurement process, enabling reduced measurement counts while maintaining image quality, with the added benefit that the masks can be implemented through simple optical elements or software algorithms.
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
Reduces power and storage needs by up to 90% through efficient measurement and compression of optical signal reflections, enabling effective image recovery with fewer measurements.
Implementation Method 1
an optical source configured to generate an optical signal and illuminate a scene with the optical signal
Implementation Method 2
measuring an amplitude of the masked reflection of the optical signal from the scene
Implementation Method 3
a spatial pattern generator configured to form masks to mask the reflection of the optical signal from the scene
Data Source
AI summary
A system includes an optical source configured to generate an optical signal and illuminate a scene with the optical signal. A first spatial pattern generator comprising pixel elements is configured to form a mask, using the pixel elements, to mask a reflection of the optical signal received from the scene. A pattern controller is coupled to the first spatial pattern generator and configured to control the pixel elements individually to form the mask, and a detector is configured to measure an amplitude of the masked reflection of the optical signal. A digitizer is coupled to the detector and configured to digitize the measured amplitude into an amplitude value. A processor coupled to the pattern controller and the digitizer is configured to instruct the first pattern controller to form a first sequence of masks to sequentially mask reflections of the optical signal using the spatial pattern generator, store the amplitude value corresponding to the measured amplitude of the masked reflection of the optical signal for each mask in the first sequence of masks, and recover an array of signals from the scene based on the stored amplitude values and the first sequence of masks, wherein a number of the stored amplitude values and a number of masks in the first sequence of masks is less than a number of signals of the array of signals.