We evaluate the performance of a multiple aperture camera with a target projector testbed and compare it to a
single lens LWIR camera with a similar field of view and pixel count. We measure a noise equivalent temperature
difference of 131 mK for the multiple aperture camera and 121 mK for the conventional camera which uses similar
uncooled 25 μm pixel technology. Spatial frequency response is analyzed using a collection of 4-bar targets with
different periods. After characterization, we remove aliasing from the multiple aperture data to resolve targets
as high as 0.192 cy/mrad.
This paper describes a compressive sensing strategy developed under the Compressive Optical MONTAGE Photography Initiative. Multiplex and multi-channel measurements are generally necessary for compressive sensing. In a compressive imaging system described here, static focal plane coding is used with multiple image apertures for non-degenerate multiplexing and multiple channel sampling. According to classical analysis, one might expect the number of pixels in a reconstructed image to equal the total number of pixels across the sampling channels, but we demonstrate that the system can achieve up to 50% compression with conventional benchmarking images. In general, the compression rate depends on the compression potential of an image with respect to the coding and decoding schemes employed in the system.
With this work we show the use of focal plane coding to produce nondegenerate data between subapertures of an imaging system. Subaperture data is integrated to form a single high resolution image. Multiple apertures generate multiple copies of a scene on the detector plane. Placed in the image plane, the focal plane mask applies a unique code to each of these sub-images. Within each sub-image, each pixel is masked so that light from only certain optical pixels reaches the detector. Thus, each sub-image measures a different linear combination of optical pixels. Image reconstruction is achieved by inversion of the transformation performed by the imaging system. Registered detector pixels in each sub-image represent the magnitude of the projection of the same optical information onto different sampling vectors. Without a coding element, the imaging system would be limited by the spatial frequency response of the electronic detector pixel. The small mask features allow the imager to broaden this response and reconstruct higher spatial frequencies than a conventional coarsely sampling focal plane.
The Compressive Optical MONTAGE Photography Initiative (COMP-I) is an initiative under DARPA's MONTAGE program. The goals of COMP-I are to produce 1 mm thick visible imaging systems and 5 mm thick IR systems without compromising pixel-limited resolution. Innovations of COMP-I include <b>focal-plane coding, block-wise focal plane codes, birefringent, holographic and 3D optical elements for focal plane remapping</b> and <b>embedded algorithms for image formation</b>. In addition to meeting MONTAGE specifications for sensor thickness, focal plane coding enables a reduction in the transverse aperture size, physical layer compression of multispectral and hyperspectral data cubes, joint optical and electronic optimization for 3D sensing, tracking, feature-specific imaging and conformal array deployment.