We use mechanical translation of a coded aperture for code division multiple access compression of video. We present experimental results for reconstruction at 148 frames per coded snapshot.

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A coded aperture snapshot spectral imager (CASSI) estimates the three-dimensional spatiospectral data cube from a snapshot two-dimensional coded projection, assuming that the scene is spatially and spectrally sparse. For less spectrally sparse scenes, we show that the use of multiple nondegenerate snapshots can make data cube recovery less ill-posed, yielding improved spatial and spectral reconstruction fidelity. Additionally, data acquisition can be easily scaled to meet the time/resolution requirements of the scene with little modification or extension of the original CASSI hardware. A multiframe reconstruction of a 640 × 480 × 53 voxel datacube with 450-650 nm white-light illumination of a scene reveals substantial improvement in the reconstruction fidelity, with limited increase in acquisition and reconstruction time.

Pixel count is the ratio of the solid angle within a camera's field of view to the solid angle covered by a single detector element. Because the size of the smallest resolvable pixel is proportional to aperture diameter and the maximum field of view is scale independent, the diffraction-limited pixel count is proportional to aperture area. At present, digital cameras operate near the fundamental limit of 1-10 megapixels for millimetre-scale apertures, but few approach the corresponding limits of 1-100 gigapixels for centimetre-scale apertures. Barriers to high-pixel-count imaging include scale-dependent geometric aberrations, the cost and complexity of gigapixel sensor arrays, and the computational and communications challenge of gigapixel image management. Here we describe the AWARE-2 camera, which uses a 16-mm entrance aperture to capture snapshot, one-gigapixel images at three frames per minute. AWARE-2 uses a parallel array of microcameras to reduce the problems of gigapixel imaging to those of megapixel imaging, which are more tractable. In cameras of conventional design, lens speed and field of view decrease as lens scale increases, but with the experimental system described here we confirm previous theoretical results suggesting that lens speed and field of view can be scale independent in microcamera-based imagers resolving up to 50 gigapixels. Ubiquitous gigapixel cameras may transform the central challenge of photography from the question of where to point the camera to that of how to mine the data.

BACKGROUND Fluorescence-guided surgery (FGS) can improve extent of resection in gliomas. Tozuleristide (BLZ-100), a near-infrared imaging agent composed of the peptide chlorotoxin and a near-infrared fluorophore indocyanine green, is a candidate molecule for FGS of glioma and other tumor types. OBJECTIVE To perform a phase 1 dose-escalation study to characterize the safety, pharmacokinetics, and fluorescence imaging of tozuleristide in adults with suspected glioma. METHODS Patients received a single intravenous dose of tozuleristide 3 to 29 h before surgery. Fluorescence images of tumor and cavity in Situ before and after resection and of excised tissue ex Vivo were acquired, along with safety and pharmacokinetic measures. RESULTS A total of 17 subjects received doses between 3 and 30 mg. No dose-limiting toxicity was observed, and no reported adverse events were considered related to tozuleristide. At doses of 9 mg and above, the terminal serum half-life for tozuleristide was approximately 30 min. Fluorescence signal was detected in both high- and low-grade glial tumors, with high-grade tumors generally showing greater fluorescence intensity compared to lower grade tumors. In high-grade tumors, signal intensity increased with increased dose levels of tozuleristide, regardless of the time of dosing relative to surgery. CONCLUSION These results support the safety of tozuleristide at doses up to 30 mg and suggest that tozuleristide imaging may be useful for FGS of gliomas.

Sophisticated methods for true spectral rendering have been developed in computer graphics to produce highly accurate images. In addition to traditional applications in visualizing appearance, such methods have potential applications in many areas of scientific study. In particular, we are motivated by the application of studying avian vision and appearance. An obstacle to using graphics in this application is the lack of reliable input data. We introduce an end-to-end measurement system for capturing spectral data on 3D objects. We present the modification of a recently developed hyperspectral imager to make it suitable for acquiring such data in a wide spectral range at high spectral and spatial resolution. We capture four megapixel images, with data at each pixel from the near-ultraviolet (359 nm) to near-infrared (1,003 nm) at 12 nm spectral resolution. We fully characterize the imaging system, and document its accuracy. This imager is integrated into a 3D scanning system to enable the measurement of the diffuse spectral reflectance and fluorescence of specimens. We demonstrate the use of this measurement system in the study of the interplay between the visual capabilities and appearance of birds. We show further the use of the system in gaining insight into artifacts from geology and cultural heritage.

Blind compressive sensing (CS) is considered for reconstruction of hyperspectral data imaged by a coded aperture camera. The measurements are manifested as a superposition of the coded wavelengthdependent data, with the ambient three-dimensional hyperspectral datacube mapped to a two-dimensional measurement. The hyperspectral datacube is recovered using a Bayesian implementation of blind CS.Several demonstration experiments are presented, including measurements performed using a coded aperture snapshot spectral imager (CASSI) camera. The proposed approach is capable of efficiently reconstructing large hyperspectral datacubes. Comparisons are made between the proposed algorithm and other techniques employed in compressive sensing, dictionary learning and matrix factorization. Index Termshyperspectral images, image reconstruction, projective transformation, dictionary learning, non-parametric Bayesian, Beta-Bernoulli model, coded aperture snapshot spectral imager (CASSI).

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