Variational Bayesian image restoration with group-sparse modeling of wavelet coefficients

In this work, we present a recent wavelet-based image restoration framework based on a group-sparse Gaussian scale mixture model. A hierarchical Bayesian estimation is derived using a combination of variational Bayesian inference and a subband-adaptive majorization–minimization method that simplifies computation of the posterior distribution. We show that both of these iterative methods can converge together without needing nested loops, and thus good solutions can be found rapidly in the non-convex search space. We also integrate our method, variational Bayesian with majorization minimization (VBMM), with tree-structured modeling of the wavelet coefficients. This extension achieves significant gains in performance over the coefficient-sparse version of the algorithm. The experimental results demonstrate that the proposed method and its tree-structured extensions are effective for various imaging applications such as image deconvolution, image superresolution and compressive sensing magnetic resonance imaging (MRI) reconstruction, and that they outperform more conventional sparsity-inducing methods based on the _l1-norm.This is the author accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S1051200415001438

Mitigating the effects of atmospheric distortion using DT-CWT fusion

This paper describes a new method for mitigating the effects of atmospheric distortion on observed images, particularly airborne turbulence which degrades a region of interest (ROI). In order to provide accurate detail from objects behind the dis-torting layer, a simple and efficient frame selection method is proposed to pick informative ROIs from only good-quality frames. We solve the space-variant distortion problem using region-based fusion based on the Dual Tree Complex Wavelet Transform (DT-CWT). We also propose an object alignment method for pre-processing the ROI since this can exhibit sig-nificant offsets and distortions between frames. Simple haze removal is used as the final step. The proposed method per-forms very well with atmospherically distorted videos and outperforms other existing methods. Index Terms — Image restoration, fusion, DT-CWT 1

The Methodology and Practice of the Evaluation of Image Retrieval Systems and Segmentation Methods

Content-Based Image Retrieval is important for two reasons. First, the oft-cited growth of image archives in many fields, and the rapid expansion of the Web, mean that successful image retrieval systems are fast becoming a necessity if the mass of accumulated data is to be useful. Second, database retrieval provides a framework within which the important questions of machine vision are brought into focus: successful retrieval is likely to require genuine image understanding. In view of these points, the evaluatio- n of retrieval systems becomes a matter of priority. There is already a substantial literature evaluating specific systems, but little high-level discussion of the evaluation methodologies themselves seems to have taken place. In the first part of the report, we propose a framework within which such issues can be addressed, analyse possible evaluation methodologies, indicate where they are appropriate and where they are not, and critique query-by-example and evaluation methodologies related to it. In the second part of the report, we apply the results of this analysis to a particular dataset. The dataset is problematic but typical: no ground truth is available for its semantics. Considering retrieval based on image segmentation- s, we present a novel method for its evaluation. Unlike methods of evaluation that rely on the existence or creation of ground truth, the proposed evaluatio- n procedure subjects human subjects to a psychovisual test comparing the results of different segmentation schemes. The test is designed to answer two questions: does consensus about a `best' segmentation exist, and if it does, what do we learn about segmentation schemes for retrieval? The results confirm that human subjects are consistent in their judgements, thus allowing meaningful evaluation

The locally stationary dual-tree complex wavelet model

We here harmonise two significant contributions to the field of wavelet analysis in the past two decades, namely the locally stationary wavelet process and the family of dual-tree complex wavelets. By combining these two components, we furnish a statistical model that can simultaneously access benefits from these two constructions. On the one hand, our model borrows the debiased spectrum and auto-covariance estimator from the locally stationary wavelet model. On the other hand, the enhanced directional selectivity is obtained from the dual-tree complex wavelets over the regular lattice. The resulting model allows for the description and identification of wavelet fields with significantly more directional fidelity than was previously possible. The corresponding estimation theory is established for the new model, and some stationarity detection experiments illustrate its practicality

Developing an inverted Barrovian sequence; insights from monazite petrochronology

In the Himalayan region of Sikkim, the well-developed inverted metamorphic sequence of the Main Central Thrust (MCT) zone is folded, thus exposing several transects through the structure that reached similar metamorphic grades at different times. In-situ LA-ICP-MS U–Th–Pb monazite ages, linked to pressure–temperature conditions via trace-element reaction fingerprints, allow key aspects of the evolution of the thrust zone to be understood for the first time. The ages show that peak metamorphic conditions were reached earliest in the structurally highest part of the inverted metamorphic sequence, in the Greater Himalayan Sequence (GHS) in the hanging wall of the MCT. Monazite in this unit grew over a prolonged period between ~37 and 16 Ma in the southerly leading-edge of the thrust zone and between ~37 and 14.5 Ma in the northern rear-edge of the thrust zone, at peak metamorphic conditions of ~790 ◦C and 10 kbar. Monazite ages in Lesser Himalayan Sequence (LHS) footwall rocks show that identical metamorphic conditions were reached ~4–6 Ma apart along the ~60 km separating samples along the MCT transport direction. Upper LHS footwall rocks reached peak metamorphic conditions of ~655 ◦C and 9 kbar between ~21 and 16 Ma in the more southerly-exposed transect and ~14.5–12 Ma in the northern transect. Similarly, lower LHS footwall rocks reached peak metamorphic conditions of ~580 ◦C and 8.5 kbar at ~16 Ma in the south, and 9–10 Ma in the north. In the southern transect, the timing of partial melting in the GHS hanging wall (~23–19.5 Ma) overlaps with the timing of prograde metamorphism (~21 Ma) in the LHS footwall, confirming that the hanging wall may have provided the heat necessary for the metamorphism of the footwall. Overall, the data provide robust evidence for progressively downwards-penetrating deformation and accretion of original LHS footwall material to the GHS hanging wall over a period of ~5 Ma. These processes appear to have occurred several times during the prolonged ductile evolution of the thrust. The preserved inverted metamorphic sequence therefore documents the formation of sequential ‘paleothrusts’ through time, cutting down from the original locus of MCT movement at the LHS–GHS protolith boundary and forming at successively lower pressure and temperature conditions. The petrochronologic methods applied here constrain a complex temporal and thermal deformation history, and demonstrate that inverted metamorphic sequences can preserve a rich record of the duration of progressive ductile thrusting

NOX1 loss-of-function genetic variants in patients with inflammatory bowel disease.

Genetic defects that affect intestinal epithelial barrier function can present with very early-onset inflammatory bowel disease (VEOIBD). Using whole-genome sequencing, a novel hemizygous defect in NOX1 encoding NAPDH oxidase 1 was identified in a patient with ulcerative colitis-like VEOIBD. Exome screening of 1,878 pediatric patients identified further seven male inflammatory bowel disease (IBD) patients with rare NOX1 mutations. Loss-of-function was validated in p.N122H and p.T497A, and to a lesser degree in p.Y470H, p.R287Q, p.I67M, p.Q293R as well as the previously described p.P330S, and the common NOX1 SNP p.D360N (rs34688635) variant. The missense mutation p.N122H abrogated reactive oxygen species (ROS) production in cell lines, ex vivo colonic explants, and patient-derived colonic organoid cultures. Within colonic crypts, NOX1 constitutively generates a high level of ROS in the crypt lumen. Analysis of 9,513 controls and 11,140 IBD patients of non-Jewish European ancestry did not reveal an association between p.D360N and IBD. Our data suggest that loss-of-function variants in NOX1 do not cause a Mendelian disorder of high penetrance but are a context-specific modifier. Our results implicate that variants in NOX1 change brush border ROS within colonic crypts at the interface between the epithelium and luminal microbes

Shift Invariant Properties Of The Dual-Tree Complex Wavelet Transform

We discuss the shift invariant properties of a new implementation of the Discrete Wavelet Transform, which employs a dual tree of wavelet filters to obtain the real and imaginary parts of complex wavelet coefficients. This introduces limited redundancy (2 m :1 for m-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. 1. INTRODUCTION The Discrete Wavelet Transform (DWT) in its maximally decimated form (Mallat's dyadic filter tree [1]) has established an impressive reputation as a tool for signal compression, but its use for other signal analysis and reconstruction tasks has been hampered by two main disadvantages: ffl Lack of shift invariance, which means that small shifts in the input signal can cause major variations i..