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A new compressive imaging camera architecture using optical-domain compression
- in Proc. of Computational Imaging IV at SPIE Electronic Imaging
, 2006
"... Compressive Sensing is an emerging field based on the revelation that a small number of linear projections of a compressible signal contain enough information for reconstruction and processing. It has many promising implications and enables the design of new kinds of Compressive Imaging systems and ..."
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Cited by 108 (10 self)
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Compressive Sensing is an emerging field based on the revelation that a small number of linear projections of a compressible signal contain enough information for reconstruction and processing. It has many promising implications and enables the design of new kinds of Compressive Imaging systems and cameras. In this paper, we develop a new camera architecture that employs a digital micromirror array to perform optical calculations of linear projections of an image onto pseudorandom binary patterns. Its hallmarks include the ability to obtain an image with a single detection element while sampling the image fewer times than the number of pixels. Other attractive properties include its universality, robustness, scalability, progressivity, and computational asymmetry. The most intriguing feature of the system is that, since it relies on a single photon detector, it can be adapted to image at wavelengths that are currently impossible with conventional CCD and CMOS imagers.
When Does Computational Imaging Improve Performance?
"... Abstract—A number of computational imaging techniques have been introduced to improve image quality by increasing light throughput. These techniques use optical coding to measure a stronger signal level. However, the performance of these techniques is limited by the decoding step, which amplifies no ..."
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Cited by 9 (4 self)
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Abstract—A number of computational imaging techniques have been introduced to improve image quality by increasing light throughput. These techniques use optical coding to measure a stronger signal level. However, the performance of these techniques is limited by the decoding step, which amplifies noise. While it is well understood that optical coding can increase performance at low light levels, little is known about the quantitative performance advantage of computational imaging in general settings. In this paper, we derive the performance bounds for various computational imaging techniques. We then discuss the implications of these bounds for several real-world scenarios (illumination conditions, scene properties and sensor noise characteristics). Our results show that computational imaging techniques do not provide a significant performance advantage when imaging with illumination brighter than typical daylight. These results can be readily used by practitioners to design the most suitable imaging systems given the application at hand.
Compound eye sensor for 3D ego motion estimation
- Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems 2004
"... Abstract — We describe a compound eye vision sensor for 3D ego motion computation. Inspired by eyes of insects, we show that the compound eye sampling geometry is optimal for 3D camera motion estimation. This optimality allows us to estimate the 3D camera motion in a scene-independent and robust man ..."
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Abstract — We describe a compound eye vision sensor for 3D ego motion computation. Inspired by eyes of insects, we show that the compound eye sampling geometry is optimal for 3D camera motion estimation. This optimality allows us to estimate the 3D camera motion in a scene-independent and robust manner by utilizing linear equations. The mathematical model of the new sensor can be implemented in analog networks resulting in a compact computational sensor for instantaneous 3D ego motion measurements in full six degrees of freedom. Key words: analog VLSI; 3D motion sensor; parallel imaging sensor; robot vision; insect vision; 3D ego motion I.
Wide-angle Micro Sensors for Vision on a Tight Budget
, 2011
"... Achieving computer vision on micro-scale devices is a challenge. On these platforms, the power and mass constraints are severe enough for even the most common computations (matrix manipulations, convolution, etc.) to be difficult. This paper proposes and analyzes a class of miniature vision sensors ..."
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Cited by 9 (1 self)
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Achieving computer vision on micro-scale devices is a challenge. On these platforms, the power and mass constraints are severe enough for even the most common computations (matrix manipulations, convolution, etc.) to be difficult. This paper proposes and analyzes a class of miniature vision sensors that can help overcome these constraints. These sensors reduce power requirements through template-based optical convolution, and they enable a wide field-of-view within a small form through a novel optical design. We describe the trade-offs between the field of view, volume, and mass of these sensors and we provide analytic tools to navigate the design space. We also demonstrate milli-scale prototypes for computer vision tasks such as locating edges, tracking targets, and detecting faces.
Performance of a MVE Algorithm for Compound Eye Image Reconstruction Using
- Lens Diversity,” Proc IEEE ICASSP 2005
, 2005
"... Reconstruction algorithms to compute a single improved resolution image from multiple lower resolution images have application in the design of cameras with flat form factors. The accuracy of these reconstructions will depend on measurement noise, measurement quantization, the structure of the image ..."
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Cited by 8 (7 self)
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Reconstruction algorithms to compute a single improved resolution image from multiple lower resolution images have application in the design of cameras with flat form factors. The accuracy of these reconstructions will depend on measurement noise, measurement quantization, the structure of the image acquisition system, and the accuracy of the image acquisition model. This paper compares the expected and simulated performance for reconstructions from multiple lower resolution images. The analysis shows that designs using lenses with different imaging characteristics significantly improve the theoretical performance results. In addition, lens diversity allows the reconstruction problem to be naturally partitioned into a set of loosely coupled smaller reconstructions that are computationally more manageable. 1.
Demonstration of an infrared microcamera inspired by Xenos Peckii vision
- Appl. Opt
, 2009
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Blind Deconvolution and Structured Matrix Computations with Applications to Array Imaging,” Blind Deconvolution: Theory and Applications
, 2007
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Stanford Tech Report CTSR 2005-02 Light Field Photography with a Hand-held Plenoptic Camera
"... This paper presents a camera that samples the 4D light field on its sensor in a single photographic exposure. This is achieved by inserting a microlens array between the sensor and main lens, creating a plenoptic camera. Each microlens measures not just the total amount of light deposited at that lo ..."
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Cited by 4 (0 self)
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This paper presents a camera that samples the 4D light field on its sensor in a single photographic exposure. This is achieved by inserting a microlens array between the sensor and main lens, creating a plenoptic camera. Each microlens measures not just the total amount of light deposited at that location, but how much light arrives along each ray. By re-sorting the measured rays of light to where they would have terminated in slightly different, synthetic cameras, we can compute sharp photographs focused at different depths. We show that a linear increase in the resolution of images under each microlens results in a linear increase in the sharpness of the refocused photographs. This property allows us to extend the depth of field of the camera without reducing the aperture, enabling shorter exposures and lower image noise. Especially in the macrophotography regime, we demonstrate that we can also compute synthetic photographs from a range of different viewpoints. These capabilities argue for a different strategy in designing photographic imaging systems. To the photographer, the plenoptic camera operates exactly like an ordinary hand-held camera. We have used our prototype to take hundreds of light field photographs, and we present examples of portraits, high-speed action and macro close-ups.
Multichannel sampling schemes for optical imaging systems
- B76-B85. SPIE-IS&T/ Vol. 8657 86570B-6 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 07/20/2015 Terms of Use: http://spiedl.org/terms
"... We introduce a framework of focal-plane coding schemes for multichannel sampling in optical systems. A particular objective is to develop an ultrathin imager without compromising image resolution. We present a complete f =2:1 optical system with a thickness of 2:2mm. The resolution is maintained in ..."
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Cited by 4 (2 self)
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We introduce a framework of focal-plane coding schemes for multichannel sampling in optical systems. A particular objective is to develop an ultrathin imager without compromising image resolution. We present a complete f =2:1 optical system with a thickness of 2:2mm. The resolution is maintained in the thin optical system by an integrated design of the encoding scheme, the process of making the coding elements, and the decoding algorithms. © 2008 Optical Society of America OCIS codes: 100.3190, 110.1758, 110.3010. 1.
