Inview Technology Corporation

Tyler H Weston

Donna E Hewitt

Robert F Bridge

Richard G Baraniuk

Lenore McMackin

Kevin F Kelly

Sujoy Chatterjee

Matthew A Herman

Byron Zollars

Justin A Fritz

Leonore McMackin

A compressive imaging system modulates an incident light stream and senses the modulated light stream to obtain compressive measurements. The measurements are algorithmically processed to reconstruct a sequence of images. The image sequence is displayed. The system receives user input (through a user interface) representing a user command to set or change one or more visual performance factors such as image quality and frame rate. The system immediately adjusts the visual performance factors by adjusting one or more underlying system parameters/algorithms. Thus, the visual consequences of any inputs to the user interface become immediately apparent in the displayed sequence of images. The user may therefore intuitively learn how to operate the user interface simply by making trial inputs and observing their effects in the displayed image sequence. The user interface may include one or more mechanical input devices and/or one or more graphical user interface (GUI) elements.

User control of the visual performance of a compressive imaging system

If a Hadamard matrix Hof order N=BF is a Kronecker product HHof an order F Hadamard matrix and an order B Hadamard matrix, then transformation by Hmay be implemented by a fast Hadamard transform at coarse scale followed by fast Hadamard transforms at fine scale. Alternatively, transformation by Hmay be achieved by performing order B transforms on columns of a two-dimensional array and order B transforms on rows of the array. As another alternative, transformation by Hmay be achieved by computing intermediate values based on linear combinations of input elements and then computing linear combinations of the intermediate values. For compressive signal acquisition, any row of Hmay be generated by concatenating selectively modified copies of a corresponding row of H. Thus, modulation patterns may be generated on the fly.

Efficient transforms and efficient row generation for Kronecker products of Hadamard matrices

A mechanism for reconstructing sub-images based on measurement data acquired by an imaging system including an array of light modulating elements and an array of photodetectors. Each sub-image is reconstructed based on samples from a respective photodetector and a respective set of measurement patterns defined on a respective virtual sub-region on the modulating array. Each virtual sub-region is configured to include at least the light modulating elements that are able to send a non-trivial amount of light to the respective photodetector during a pattern application period. The virtual sub-regions overlap because many light modulating elements are capable of sending light to more than one photodetector. Whenever a measurement pattern of one virtual sub-region overlaps the measurement pattern of a neighboring virtual sub-region, the two measurement patterns agree by design. Thus, the measurement patterns for the collection of virtual sub-regions combine to form a pattern on the whole modulating array.

Overlap patterns and image stitching for multiple-detector compressive-sensing camera

Mechanisms for increasing the rate of acquisition of compressed/encoded image representations are disclosed. An imaging system may deliver subsets of a modulated light stream onto respective light sensing devices. The light sensing devices may be sampled in parallel. Samples from each light sensing device may be used to construct a respective sub-image of a final image. The parallelism allows compressed images to be acquired at a higher rate. The number of light sensing devices and/or the number of pixels per image may be selected to achieve a target image acquisition rate. In another embodiment, spatial portions of the incident light stream are separated and delivered to separate light modulators. In yet another embodiment, the incident light stream is split into a plurality of beams, each of which retains the image present in the incident light stream and is delivered to a separate light modulator.

Decreasing image acquisition time for compressive imaging devices

An imaging system and method that captures compressive sensing (CS) measurements of a received light stream, and also obtains samples of background light level (BGLL). The BGLL samples may be used to compensate the CS measurements for variations in the BGLL. The system includes: a light modulator to spatially modulate the received light stream with spatial patterns, and a lens to concentrate the modulated light stream onto a light detector. The samples of BGLL may be obtained in various ways: (a) injecting calibration patterns among the spatial patterns; (b) measuring complementary light reflected by digital micromirrors onto a secondary output path; (c) separating and measuring a portion of light from the optical input path; (d) low-pass filtering the CS measurements; and (e) employing a light power meter with its own separate input path. Also, the CS measurements may be high-pass filtered to attenuate background light variation.

Compensation of compressive imaging measurements based on measurements from power meter

A system and method for searching an incident light field for atypical regions (e.g., hot spots or cool spots or spectrally distinctive regions) within the incident light field using a light modulator and a spectral sensing device. Once the atypical regions are identified, the light modulator may be used to mask the incident light field so that the spectral sensing device can make spatially-concentrated measurements of the wavelength spectrum of the atypical regions (or alternatively, the exterior of the atypical regions). Furthermore, in a compressive imaging mode, a sequence of spatial patterns may be supplied to the light modulator, and a corresponding sequence of wavelength spectra may be collected from the spectral sensing device. The wavelength spectra comprise a compressed representation of the incident light field over space and wavelength. The wavelength spectra may be used to reconstruct a multispectral (or hyperspectral) data cube.

Adaptive search for atypical regions in incident light field and spectral classification of light in the atypical regions

A compressive imaging (CI) device including a light modulator and a light sensor (e.g., a single-element sensor or a sensor array). The CI device may support the focusing of light on the light modulator and/or on the light sensor in a number of ways: (1) determining a focus indicator value by analyzing a 1D or 2D image in the incident light field; (2) measuring light spillover between modulator regions and light sensing elements&#x2014;either at the level of voltage measurements or the level of reconstructed images; (3) measure noise in reconstructed sub-images; (4) measuring an amount high-frequency content in the incident light field; (5) incorporating a range finder to measure distance to the object being imaged; (6) incorporating an image sensor downstream from the modulator; and (7) splitting a portion of the incident light onto an image sensor, prior to the modulator.

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Austin, TX, United States of America

Tyler H Weston