Releasing aperture filter constraints

Aperture filters are a recently introduced class of nonlinear filters used in image processing. In this paper we present a new approach for aperture filter design, improving operator performance with respect to the MSE measure by releasing some of the operator constraints without losing statistical estimation accuracy. With the use of the proposed methods an average of 34% MSE reduction was achieved for deblurring, whereas a standard aperture operator reduced the error by only 10% on the average

Joint demosaicing and fusion of multiresolution coded acquisitions: A unified image formation and reconstruction method

Novel optical imaging devices allow for hybrid acquisition modalities such as compressed acquisitions with locally different spatial and spectral resolutions captured by a single focal plane array. In this work, we propose to model the capturing system of a multiresolution coded acquisition (MRCA) in a unified framework, which natively includes conventional systems such as those based on spectral/color filter arrays, compressed coded apertures, and multiresolution sensing. We also propose a model-based image reconstruction algorithm performing a joint demosaicing and fusion (JoDeFu) of any acquisition modeled in the MRCA framework. The JoDeFu reconstruction algorithm solves an inverse problem with a proximal splitting technique and is able to reconstruct an uncompressed image datacube at the highest available spatial and spectral resolution. An implementation of the code is available at https://github.com/danaroth83/jodefu.Comment: 15 pages, 7 figures; regular pape

The Atlas Structure of Images

Many operations of vision require image regions to be isolated and inter-related. This is challenging when they are different in detail and extent. Practical methods of Computer Vision approach this through the tools of downsampling, pyramids, cropping and patches. In this paper we develop an ideal geometric structure for this, compatible with the existing scale space model of image measurement. Its elements are apertures which view the image like fuzzy-edged portholes of frosted glass. We establish containment and cause/effect relations between apertures, and show that these link them into cross-scale atlases. Atlases formed of Gaussian apertures are shown to be a continuous version of the image pyramid used in Computer Vision, and allow various types of image description to naturally be expressed within their framework. We show that views through Gaussian apertures are approximately equivalent to the jets of derivative of Gaussian filter responses that form part of standard Scale Space theory. This supports a view of the simple cells of mammalian V1 as implementing a system of local views of the retinal image of varying extent and resolution. As a worked example we develop a keypoint descriptor scheme that outperforms previous schemes that do not make use of learning

An Approach to Ground Moving Target Indication Using Multiple Resolutions of Multilook Synthetic Aperture Radar Images

Ground moving target indication (GMTI) using multiple resolutions of synthetic aperture radar (SAR) images to estimate the clutter scattering statistics is shown to outperform conventional sample matrix inversion space-time adaptive processing GMTI techniques when jamming is not present. A SAR image provides an estimate of scattering from nonmoving targets in the form of a clutter scattering covariance matrix for the GMTI optimum processor. Since the homogeneity of the scattering statistics are unknown, using SAR images at multiple spatial resolutions to estimate the clutter scattering statistics results in more confidence in the final detection decision. Two approaches to calculating the multiple SAR resolutions are investigated. Multiple resolution filter bank smoothing of the full-resolution SAR image is shown to outperform an innovative approach to multilook SAR imaging. The multilook SAR images are calculated from a single measurement vector partitioned base on synthetic sensor locations determined via eigenanalysis of the radar measurement parameters

A New X-ray Selected Sample of Very Extended Galaxy Groups from the ROSAT All-Sky Survey

Some indications for tension have long been identified between cosmological constraints obtained from galaxy clusters and primary CMB measurements. Typically, assuming the matter density and fluctuations, as parameterized with Omega_m and sigma_8, estimated from CMB measurements, many more clusters are expected than those actually observed. One possible explanation could be that certain types of galaxy groups or clusters were missed in samples constructed in previous surveys, resulting in a higher incompleteness than estimated. We aim to determine if a hypothetical class of very extended, low surface brightness, galaxy groups or clusters have been missed in previous X-ray cluster surveys based on the ROSAT All-Sky Survey (RASS). We applied a dedicated source detection algorithm sensitive also to more unusual group or cluster surface brightness distributions. We found many known but also a number of new group candidates, which are not included in any previous X-ray / SZ cluster catalogs. In this paper, we present a pilot sample of 13 very extended groups discovered in the RASS at positions where no X-ray source has been detected previously and with clear optical counterparts. The X-ray fluxes of at least 5 of these are above the nominal flux-limits of previous RASS cluster catalogs. They have low mass ($10^{13} - 10^{14} M_{\odot}$; i.e., galaxy groups), are at low redshift (z<0.08), and exhibit flatter surface brightness distributions than usual. We demonstrate that galaxy groups were missed in previous RASS surveys, possibly due to the flat surface brightness distributions of this potential new population. Analysis of the full sample will show if this might have a significant effect on previous cosmological parameter constraints based on RASS cluster surveys. (This is a shortened version of the abstract - full text in the article)Comment: 18 pages, 7 figures, accepted by A&

Exploring scatterer anisotrophy in synthetic aperture radar via sub-aperture analysis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 189-193).Scattering from man-made objects in SAR imagery exhibits aspect and frequency dependencies which are not always well modeled by standard SAR imaging techniques based on the ideal point scattering model. This is particularly the case for highresolution wide-band and wide-aperture data where model deviations are even more pronounced. If ignored, these deviations will reduce recognition performance due to the model mismatch, but when appropriately accounted for, these deviations from the ideal point scattering model can be exploited as attributes to better distinguish scatterers and their respective targets. With this in mind, this thesis develops an efficient modeling framework based on a sub-aperture pyramid to utilize scatterer anisotropy for the purpose of target classification. Two approaches are presented to exploit scatterer anisotropy using the sub-aperture pyramid. The first is a nonparametric classifier that learns the azimuthal dependencies within an image and makes a classification decision based on the learned dependencies. The second approach is a parametric attribution of the observed anisotropy characterizing the azimuthal location and concentration of the scattering response. Working from the sub-aperture scattering model, we develop a hypothesis test to characterize anisotropy. We start with an isolated scatterer model which produces a test with an intuitive interpretation. We then address the problem of robustness to interfering scatterers by extending the model to account for neighboring scatterers which corrupt the anisotropy attribution.(cont.) The development of the anisotropy attribution culminates with an iterative attribution approach that identifies and compensates for neighboring scatterers. In the course of the development of the anisotropy attribution, we also study the relationship between scatterer phenomenology and our anisotropy attribution. This analysis reveals the information provided by the anisotropy attribution for two common sources of anisotropy. Furthermore, the analysis explicitly demonstrates the benefit of using wide-aperture data to produce more stable and more descriptive characterizations of scatterer anisotropy.y Andrew J. Kim.Ph.D

Coded aperture imaging

This thesis studies the coded aperture camera, a device consisting of a conventional camera with a modified aperture mask, that enables the recovery of both depth map and all-in-focus image from a single 2D input image. Key contributions of this work are the modeling of the statistics of natural images and the design of efficient blur identification methods in a Bayesian framework. Two cases are distinguished: 1) when the aperture can be decomposed in a small set of identical holes, and 2) when the aperture has a more general configuration. In the first case, the formulation of the problem incorporates priors about the statistical variation of the texture to avoid ambiguities in the solution. This allows to bypass the recovery of the sharp image and concentrate only on estimating depth. In the second case, the depth reconstruction is addressed via convolutions with a bank of linear filters. Key advantages over competing methods are the higher numerical stability and the ability to deal with large blur. The all-in-focus image can then be recovered by using a deconvolution step with the estimated depth map. Furthermore, for the purpose of depth estimation alone, the proposed algorithm does not require information about the mask in use. The comparison with existing algorithms in the literature shows that the proposed methods achieve state-of-the-art performance. This solution is also extended for the first time to images affected by both defocus and motion blur and, finally, to video sequences with moving and deformable objects