2,902 research outputs found
Rational-operator-based depth-from-defocus approach to scene reconstruction
This paper presents a rational-operator-based approach to depth from defocus (DfD) for the reconstruction of three-dimensional scenes from two-dimensional images, which enables fast DfD computation that is independent of scene textures. Two variants of the approach, one using the Gaussian rational operators (ROs) that are based on the Gaussian point spread function (PSF) and the second based on the generalized Gaussian PSF, are considered. A novel DfD correction method is also presented to further improve the performance of the approach. Experimental results are considered for real scenes and show that both approaches outperform existing RO-based methods
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs
Human visual system relies on both binocular stereo cues and monocular
focusness cues to gain effective 3D perception. In computer vision, the two
problems are traditionally solved in separate tracks. In this paper, we present
a unified learning-based technique that simultaneously uses both types of cues
for depth inference. Specifically, we use a pair of focal stacks as input to
emulate human perception. We first construct a comprehensive focal stack
training dataset synthesized by depth-guided light field rendering. We then
construct three individual networks: a Focus-Net to extract depth from a single
focal stack, a EDoF-Net to obtain the extended depth of field (EDoF) image from
the focal stack, and a Stereo-Net to conduct stereo matching. We show how to
integrate them into a unified BDfF-Net to obtain high-quality depth maps.
Comprehensive experiments show that our approach outperforms the
state-of-the-art in both accuracy and speed and effectively emulates human
vision systems
Weak Lensing from Space I: Instrumentation and Survey Strategy
A wide field space-based imaging telescope is necessary to fully exploit the
technique of observing dark matter via weak gravitational lensing. This first
paper in a three part series outlines the survey strategies and relevant
instrumental parameters for such a mission. As a concrete example of hardware
design, we consider the proposed Supernova/Acceleration Probe (SNAP). Using
SNAP engineering models, we quantify the major contributions to this
telescope's Point Spread Function (PSF). These PSF contributions are relevant
to any similar wide field space telescope. We further show that the PSF of SNAP
or a similar telescope will be smaller than current ground-based PSFs, and more
isotropic and stable over time than the PSF of the Hubble Space Telescope. We
outline survey strategies for two different regimes - a ``wide'' 300 square
degree survey and a ``deep'' 15 square degree survey that will accomplish
various weak lensing goals including statistical studies and dark matter
mapping.Comment: 25 pages, 8 figures, 1 table, replaced with Published Versio
Highlighting objects of interest in an image by integrating saliency and depth
Stereo images have been captured primarily for 3D reconstruction in the past.
However, the depth information acquired from stereo can also be used along with
saliency to highlight certain objects in a scene. This approach can be used to
make still images more interesting to look at, and highlight objects of
interest in the scene. We introduce this novel direction in this paper, and
discuss the theoretical framework behind the approach. Even though we use depth
from stereo in this work, our approach is applicable to depth data acquired
from any sensor modality. Experimental results on both indoor and outdoor
scenes demonstrate the benefits of our algorithm
Thon rings from amorphous ice and implications of beam-induced Brownian motion in single particle electron cryo-microscopy
We have recorded dose-fractionated electron cryo-microscope images of thin
films of pure flash-frozen amorphous ice and pre-irradiated amorphous carbon on
a Falcon~II direct electron detector using 300 keV electrons. We observe Thon
rings \cite{Thon1966} in both the power spectrum of the summed frames and the
sum of power spectra from the individual frames. The Thon rings from amorphous
carbon images are always more visible in the power spectrum of the summed
frames whereas those of amorphous ice are more visible in the sum of power
spectra from the individual frames. This difference indicates that while
pre-irradiated carbon behaves like a solid during the exposure, amorphous ice
behaves like a fluid with the individual water molecules undergoing
beam-induced motion. Using the measured variation in the power spectra
amplitude with number of electrons per image we deduce that water molecules are
randomly displaced by mean squared distance of 1.1 \AA for every
incident 300 keV e/\AA. The induced motion leads to an optimal
exposure with 300 keV electrons of 4.0 e/\AA per image with which to
see Thon rings centred around the strong 3.7{\AA} scattering peak from
amorphous ice. The beam-induced movement of the water molecules generates
pseudo-Brownian motion of embedded macromolecules. The resulting blurring of
single particle images contributes an additional term, on top of that from
radiation damage, to the minimum achievable B-factor for macromolecular
structure determination.Comment: 11 pages, 6 figures, Supplementary information 6 pages with 5 figure
Robust visualization and discrimination of nanoparticles by interferometric imaging
Single-molecule and single-nanoparticle biosensors are a growing frontier in diagnostics. Digital biosensors are those which enumerate all specifically immobilized biomolecules or biological nanoparticles, and thereby achieve limits of detection usually beyond the reach of ensemble measurements. Here we review modern optical techniques for single nanoparticle detection and describe the single-particle interferometric reflectance imaging sensor (SP-IRIS). We present challenges associated with reliably detecting faint nanoparticles with SP-IRIS, and describe image acquisition processes and software modifications to address them. Specifically, we describe a image acquisition processing method for the discrimination and accurate counting of nanoparticles that greatly reduces both the number of false positives and false negatives. These engineering improvements are critical steps in the translation of SP-IRIS towards applications in medical diagnostics.R01 AI096159 - NIAID NIH HHSFirst author draf
- …