Image Sequence Reconstruction based on Overlapping Measurement Subsets

Abstract

A compressive imaging mechanism for increasing the rate at which images can be acquired and reconstructed. An incident light stream is modulated with a time sequence of spatial patterns using a light modulator. The modulated light stream is sensed with a light sensor to obtain a time sequence (stream) of measurements. Overlapping subsets of the measurements are generated at a rate that equals a desired image rate. Each of the subsets is processed to algorithmically reconstruct a corresponding image, preferably with bounded latency. The resulting images are displayed at the desired image rate. The modulation, sensing, subset generation, reconstruction and display may be arranged as a continuous pipeline process. Different images rates may be achieved by changing the amount of overlap between the subsets.

Description

RELATED APPLICATION DATA[0001]This application claims the benefit of priority to U.S. Provisional Application No. 61 / 502,153, filed on Jun. 28, 2011, entitled “Various Compressive Sensing Mechanisms”, invented by Tidman, Weston, Bridge, McMackin, Chatterjee, Woods, Baraniuk and Kelly, which is hereby incorporated by reference in its entirety as though fully and completely set forth herein.FIELD OF THE INVENTION[0002]The present invention relates to the field of compressive imaging, and more particularly, to mechanisms for accelerating the rate at which compressive imaging devices can acquire and reconstruct sequences of images.DESCRIPTION OF THE RELATED ART[0003]According to Nyquist theory, a signal x(t) whose signal energy is supported on the frequency interval [−B,B] may be reconstructed from samples {x(nT)} of the signal x(t), provided the rate fS=1 / TS at which the samples are captured is sufficiently high, i.e., provided that fS is greater than 2B. Similarly, for a signal whose ...

AI Technical Summary

Benefits of technology

[0022]In some embodiments, the input data set for the reconstruction of a current image of the image sequence may also include a previously-reconstructed image of the image sequence. The previously-reconstructed image serves as an initial estimate for the current image, and, may allow the reconstruction algorithm to converge faster to its final estimate for the current image than if no initial estimate were provided.

Problems solved by technology

A fundamental problem with any attempt to capture a signal x(t) according to Nyquist theory is the large number of samples that are generated, especially when B (or B−A) is large.

The same problem of overwhelming data volume is experienced when attempting to capture an image according to Nyquist theory.

One of the challenges in compressive imaging is acquiring the sample subsets fast enough to compete with conventional cameras that employ array-based light sensors (such as focal plane arrays, CCD arrays, etc.), and therefore, are able to non-compressively acquire images at video rates.

In a compressive imaging system, the rate of acquisition of the sample subsets may be limited by the rate at which the light modulator can be reconfigured.

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