Inview Technology Corporation

Matthew A Herman

Tyler H Weston

Donna E Hewitt

Lenore McMackin

Robert F Bridge

Justin A Fritz

Thomas A Goldstein

A mechanism for reconstructing a signal (e.g., an image) based on a vector s, which includes measurements of the signal. The measurements have been acquired using at least a portion of a measurement vector set represented by a matrix H. Each of the measurements corresponds to a respective row of the matrix H. (For example, each of the measurements may correspond to an inner product between the signal and a respective row of the matrix product HD, wherein D is a generalized permutation matrix.) A total-variation primal-dual hybrid gradient (TV-PDHG) algorithm is executed based on data including the matrix H and the vector s, to determine an estimate for the signal. The TV-PDHG algorithm is implemented in fixed-point arithmetic.

Signal reconstruction using total-variation primal-dual hybrid gradient (TV-PDHG) algorithm

A methodology for acquiring measurements of a signal at one or more scales of resolution, including: generating modulation patterns based on a predefined measurement matrix; modulating a received signal with the modulation patterns using the signal modulating array to obtain a modulated signal; and acquiring measurements of intensity of the modulated signal. Each modulation pattern is generated by: (a) selecting a corresponding row of the measurement matrix; (b) reordering elements of the selected row according to a permutation to obtain a reordered row; and (c) transferring the reordered row to the signal modulating array so that elements of the reordered row are mapped onto the signal modulating array. The permutation is defined so that a subset of the modulation patterns are coarse patterns that respect a partition of the signal modulating array into an array of superpixels, each superpixel including a respective group of the signal modulating elements.

Generating modulation patterns for the acquisition of multiscale information in received signals

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

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.

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Austin, TX, United States of America

Matthew A Herman