Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Effect of flow-geometry on turbulence-scalar interaction in premixed flames

Turbulent combustion of stoichiometric hydrogen-air mixture is simulated using direct numerical simulation methodology, employing complex chemical kinetics. Two flame configurations, freely propagating and V-flames stabilized behind a hot rod, are simulated. The results are analyzed to study the influence of flame configuration on the turbulence-scalar interaction, which is critical for the scalar gradient generation processes. The result suggests that this interaction process is not influenced by the flame configuration and the flame normal is found to align with the most extensive strain in the region of intense heat release. The combustion in the rod stabilized flame is found to be flamelet like in an average sense and the growth of flame-brush thickness with the downstream distance is represented well by Taylor theory of turbulent diffusion, when the flame-brushes are non-interacting. The thickness is observed to saturate when the flame-brushes interact, which is found to occur in the simulated rod stabilized flame with Taylor micro-scale Reynolds number of 97. © 2011 American Institute of Physics.

Automatic object segmentation from calibrated images

This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape representation of a potentially texture-less object by computing a visual hull. We propose an automatic approach where the object to be segmented is identified by the pose of the cameras instead of user input such as 2D bounding rectangles or brush-strokes. The key behind our method is a pairwise MRF framework that combines (a) foreground/background appearance models, (b) epipolar constraints and (c) weak stereo correspondence into a single segmentation cost function that can be efficiently solved by Graph-cuts. The segmentation thus obtained is further improved using silhouette coherency and then used to update the foreground/background appearance models which are fed into the next Graph-cut computation. These two steps are iterated until segmentation convergences. Our method can automatically provide a 3D surface representation even in texture-less scenes where MVS methods might fail. Furthermore, it confers improved performance in images where the object is not readily separable from the background in colour space, an area that previous segmentation approaches have found challenging. © 2011 IEEE.

Optimization of nanotube electrode geometry in a liquid crystal media from wavefront aberrations

This paper presents experimental optimization of number and geometry of nanotube electrodes in a liquid crystal media from wavefront aberrations for realizing nanophotonic devices. The refractive-index gradient profiles from different nanotube geometries-arrays of one, three, four, and five-were studied along with wavefront aberrations using Zernike polynomials. The optimizations help the device to make application in the areas of voltage reconfigurable microlens arrays, high-resolution displays, wavefront sensors, holograms, and phase modulators. © 2012 Optical Society of America.

Effects of flow geometry and Damkohler number on turbulent premixed flame

DNS of planar turbulent flame and turbulent V-flame has been conducted to investigate turbulence-scalar interaction in relatively practical turbulent combustion. Several turbulence quantities are examined for the understandings of fundamental characteristics of flow field in V-flame. Due to the additional turbulence production by the hot-rod, turbulence does not simply decay in V-flame. Turbulence-scalar interaction, scalar alignments with the principal strain rate in other words, is then clarified. The competition of turbulence and dilatation can be found in the conditional PDF of flame normal alignment. The results suggests that the alignment characteristics in high Da flames are applicable to low Da flames in the region of intense heat release.

Color photometric stereo for multicolored surfaces

We present a multispectral photometric stereo method for capturing geometry of deforming surfaces. A novel photometric calibration technique allows calibration of scenes containing multiple piecewise constant chromaticities. This method estimates per-pixel photometric properties, then uses a RANSAC-based approach to estimate the dominant chromaticities in the scene. A likelihood term is developed linking surface normal, image intensity and photometric properties, which allows estimating the number of chromaticities present in a scene to be framed as a model estimation problem. The Bayesian Information Criterion is applied to automatically estimate the number of chromaticities present during calibration. A two-camera stereo system provides low resolution geometry, allowing the likelihood term to be used in segmenting new images into regions of constant chromaticity. This segmentation is carried out in a Markov Random Field framework and allows the correct photometric properties to be used at each pixel to estimate a dense normal map. Results are shown on several challenging real-world sequences, demonstrating state-of-the-art results using only two cameras and three light sources. Quantitative evaluation is provided against synthetic ground truth data. © 2011 IEEE.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.