Systems and methods for implementing array cameras configured to perform super- resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. Lens stack arrays in accordance with many embodiments of the invention include lens elements formed on substrates separated by spacers, where the lens elements, substrates and spacers are configured to form a plurality of optical channels, at least one aperture located within each optical channel, at least one spectral filter located within each optical channel, where each spectral filter is configured to pass a specific spectral band of light, and light blocking materials located within the lens stack array to optically isolate the optical channels.

Capturing and processing of images using monolithic camera array with heterogeneous imagers

The emerging field of compressed sensing has potentially powerful implications for the design of optical imaging devices In particular, compressed sensing theory suggests that one can recover a scene at a higher resolution than is dictated by the pitch of the focal plane array This rather remarkable result comes with some important caveats however, especially when practical issues associated with physical implementation are taken into account This tutorial discusses compressed sensing in the context of optical imaging devices, emphasizing the practical hurdles related to building such devices, and offering suggestions for overcoming these hurdles Examples and analysis specifically related to infrared imaging highlight the challenges associated with large format focal plane arrays and how these challenges can be mitigated using compressed sensing ideas

https://www.spiedigitallibrary.org/journals/optical-engineering/volume-50/issue-7/072601/Compressed-sensing-for-practical-optical-imaging-systems-a-tutorial/10.1117/1.3596602.pdf

Compressed sensing for practical optical imaging systems: a tutorial

Systems and methods are described for generating restricted depth of field depth maps. In one embodiment, an image processing pipeline application configures a processor to: determine a desired focal plane distance and a range of distances corresponding to a restricted depth of field for an image rendered from a reference viewpoint; generate a restricted depth of field depth map from the reference viewpoint using the set of images captured from different viewpoints, where depth estimation precision is higher for pixels with depth estimates within the range of distances corresponding to the restricted depth of field and lower for pixels with depth estimates outside of the range of distances corresponding to the restricted depth of field; and render a restricted depth of field image from the reference viewpoint using the set of images captured from different viewpoints and the restricted depth of field depth map.

Systems and Methods for Synthesizing Images from Image Data Captured by an Array Camera Using Restricted Depth of Field Depth Maps in which Depth Estimation Precision Varies

We propose a microoptical approach to ultra-compact optics for real-time vision systems that are inspired by the compound eyes of insects. The demonstrated module achieves approx. VGA resolution with a total track length of 1.4 mm which is about two times shorter than comparable single-aperture optics on images sensors of the same pixel pitch. The partial images that are separately recorded in different optical channels are stitched together to form a final image of the whole field of view by means of image processing. A software correction is applied to each partial image so that the final image is made free of distortion. The microlens arrays are realized by state of the art microoptical fabrication techniques on wafer-level which are suitable for a potential application in high volume e.g. for consumer electronic products.

Thin wafer-level camera lenses inspired by insect compound eyes

Preface. Acknowledgments. 1. Past, present and future. 1.1 Three revolutions. 1.2 Computational imaging. 1.3 Overview. 1.4 The fourth revolution. Problems. 2. Geometric imaging. 2.1 Visibility. 2.2 Optical elements. 2.3 Focal imaging. 2.4 Imaging systems. 2.5 Pinhole and coded aperture imaging. 2.6 Projection tomography. 2.7 Reference structure tomography. Problems. 3. Analysis. 3.1 Analytical tools. 3.2 Fields and transformations. 3.3 Fourier analysis. 3.4 Transfer functions and filters. 3.5 The Fresnel transformation. 3.6 The Whittaker-Shannon sampling theorem. 3.7 Discrete analysis of linear transformations. 3.8 Multiscale sampling. 3.9 B-splines. 3.10 Wavelets. Problems. 4. Wave imaging. 4.1 Waves and fields. 4.2 Wave model for optical fields. 4.3 Wave propagation. 4.4 Diffraction. 4.5 Wave analysis of optical elements. 4.6 Wave propagation through thin lenses. 4.7 Fourier analysis of wave imaging. 4.8 Holography. Problems. 5. Detection. 5.1 The Optoelectronic interface. 5.2 Quantum mechanics of optical detection. 5.3 Optoelectronic detectors. 5.3.1 Photoconductive detectors. 5.3.2 Photodiodes. 5.4 Physical characteristics of optical detectors. 5.5 Noise. 5.6 Charge coupled devices. 5.7 Active pixel sensors. 5.8 Infrared focal plane arrays. Problems. 6. Coherence imaging. 6.1 Coherence and spectral fields. 6.2 Coherence propagation. 6.3 Measuring coherence. 6.4 Fourier analysis of coherence imaging. 6.5 Optical coherence tomography. 6.6 Modal analysis. 6.7 Radiometry. Problems. 7. Sampling. 7.1 Samples and pixels. 7.2 Image plane sampling on electronic detector arrays. 7.3 Color imaging. 7.4 Practical sampling models. 7.5 Generalized sampling. Problems. 8. Coding and inverse problems. 8.1 Coding taxonomy. 8.2 Pixel coding. 8.3 Convolutional coding. 8.4 Implicit coding. 8.5 Inverse problems. Problems. 9. Spectroscopy. 9.1 Spectral measurements. 9.2 Spatially dispersive spectroscopy. 9.3 Coded aperture spectroscopy. 9.4 Interferometric Spectroscopy. 9.5 Resonant spectroscopy. 9.6 Spectroscopic filters. 9.7 Tunable filters. 9.8 2D spectroscopy. Problems. 10. Computational imaging. 10.1 Imaging systems. 10.2 Depth of field. 10.3 Resolution. 10.4 Multiple aperture imaging. 10.5 Generalized sampling revisited. 10.6 Spectral imaging. Problems. References.

/pdf/optical-imaging-and-spectroscopy-a4kerixevm.pdf

Optical Imaging and Spectroscopy

A color camera includes at least three sub-cameras, each sub-camera having an imaging lens, a color filter, and an array of detectors, The color camera combines images from the three sub-cameras to form a composite multi-color image, wherein the three sub-cameras include a total number of detectors N and a total number of different color sets X, wherein a first number of signals of a first color set is less than N/X and a second number of signals of a second color set is greater than N/X, signals of the second color set being output from at least two of the three sub-cameras, wherein resolution of a composite image of the second color set is greater than resolution of an individual sub-camera and a resolution of the composite image. Corresponding images of the same color set may be shifted, either sequentially or simultaneously, relative to one another.

Thin color camera

The size of infrared camera systems can be reduced by collecting low-resolution images in parallel with multiple narrow-aperture lenses rather than collecting a single high-resolution image with one wide-aperture lens. We describe an infrared imaging system that uses a three-by-three lenslet array with an optical system length of 2.3 mm and achieves Rayleigh criteria resolution comparable with a conventional single-lens system with an optical system length of 26 mm. The high-resolution final image generated by this system is reconstructed from the low-resolution images gathered by each lenslet. This is accomplished using superresolution reconstruction algorithms based on linear and nonlinear interpolation algorithms. Two implementations of the ultrathin camera are demonstrated and their performances are compared with that of a conventional infrared camera.

/pdf/thin-infrared-imaging-systems-through-multichannel-sampling-3gg03hk954.pdf

Thin infrared imaging systems through multichannel sampling

A method of fabricating a diffractive optical element includes the steps of: etching a negative of a desired multi-level diffraction pattern onto a molding surface of a quartz master element using photolithography, assembling the master element as a portion of a mold, and injecting a plastic molding composition into the mold and against the molding surface of the master element to injection mold a diffractive optical element, whereby the optical element has the desired diffraction pattern on its surface. The diffraction pattern is preferably formed on the quartz master using VLSI photolithography.

Molding diffractive optical elements

A soft aperture allows gradual attenuation of a light beam dependent upon its location away from the center of a diffractive optical element. Such an optical element may be provided by decreasing a number of phase levels, increasing a number of phase levels, increasing a density of metal patches or diffractive gratings, or decreasing a blaze height and/or duty cycle, all radially from the center. Alternatively, the soft aperture may be defined by a photolithographic process. Such a soft aperture is particularly useful in aiding circularizing of an elliptical light beam. The soft aperture may be used alone or integrated with other optical elements.

Optical soft aperture and use thereof

A sub-wavelength anti-reflective diffractive structure is incorporated with a base diffractive structure having a small period to form a high efficiency diffractive structure. In the high efficiency diffractive structure, the anti-reflective structure and/or the base diffractive structure are altered from their ideal solo structure to provide both the desired performance and minimize reflections.

Robert Te Kolste

Papers

Thin color camera

Thin infrared imaging systems through multichannel sampling

Molding diffractive optical elements

Optical soft aperture and use thereof

Reduced loss high efficiency diffractive and associated methods