Monocentric lenses provide high-resolution wide field of view imaging onto a hemispherical image surface, which can be coupled to conventional focal planes using fiber-bundle image transfer. We show the design and characterization of a 2-glass concentric F/1.0 lens, and describe integration of 5 Mpixel 1.75µm pitch back-side illuminated color CMOS sensors with 2.5µm pitch fiber bundles, then show the fiber-coupled lens compares favorably in both resolution and light collection to a 10x larger conventional F/4 wide angle photographic lens. We describe assembly of the monocentric lens and 6 adjacent sensors with focus optomechanics into an extremely compact 30Mpixel panoramic imager with a 126° "letterbox" format field of view.
Monocentric lenses have proven exceptionally capable of high numerical aperture wide-field imaging-provided the overall system can accommodate a spherically curved image surface. We will present a summary of recent work on the design optimization and experimental demonstrations of monocentric wide-field imaging, including systems based on waveguide coupling of the image to conventional focal plane sensor(s).
Some high-performance imaging systems generate a curved focal surface and so are incompatible with focal plane arrays fabricated by conventional silicon processing. One example is a monocentric lens, which forms a wide field-of-view high-resolution spherical image with a radius equal to the focal length. Optical fiber bundles have been used to couple between this focal surface and planar image sensors. However, such fiber-coupled imaging systems suffer from artifacts due to image sampling and incoherent light transfer by the fiber bundle as well as resampling by the focal plane, resulting in a fixed obscuration pattern. Here, we describe digital image processing techniques to improve image quality in a compact 126° field-of-view, 30 megapixel panoramic imager, where a 12 mm focal length F/1.35 lens made of concentric glass surfaces forms a spherical image surface, which is fiber-coupled to six discrete CMOS focal planes. We characterize the locally space-variant system impulse response at various stages: monocentric lens image formation onto the 2.5 μm pitch fiber bundle, image transfer by the fiber bundle, and sensing by a 1.75 μm pitch backside illuminated color focal plane. We demonstrate methods to mitigate moiré artifacts and local obscuration, correct for sphere to plane mapping distortion and vignetting, and stitch together the image data from discrete sensors into a single panorama. We compare processed images from the prototype to those taken with a 10× larger commercial camera with comparable field-of-view and light collection.
Compressive imagers acquire images, or other optical scene information, by a series of spatially filtered intensity measurements, where the total number of measurements required depends on the desired image quality. Compressive imaging (CI) offers a versatile approach to optical sensing which can improve size, weight, and performance (SWaP) for multispectral imaging or feature-based optical sensing. Here we report the first (to our knowledge) systematic performance comparison of a CI system to a conventional focal plane imager for binary, grayscale, and natural light (visible color and infrared) scenes. We generate 1024 × 1024 images from a range of measurements (0.1%-100%) acquired using digital (Hadamard), grayscale (discrete cosine transform), and random (Noiselet) CI basis sets. Comparing the outcome of the compressive images to conventionally acquired images, each made using 1% of full sampling, we conclude that the Hadamard Transform offered the best performance and yielded images with comparable aesthetic quality and slightly higher spatial resolution than conventionally acquired images.
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