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GPU hardware architectures have evolved into a suitable platform for the hardware acceleration of complex computing tasks. Stereo vision is one such task where acceleration is desirable for robotic and automotive systems. Much research was invested in developing stereo vision algorithms with increased quality, but real-time implementations are still lacking. In this work we focus on creating a real-time...
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves great improvement on the qualities of the solutions in some applications such as stereo matching and optical flow. In continuous formulation, however, it is much more difficult to optimize the target functions. In this paper,...
GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, which allows them to handle complex scenes including moving trees, flags moving in the wind etc. However, it is not always easy to determine which distributions of the mixture belong to the background and which distributions...
Shift-map image processing is a new framework based on energy minimization over a large space of labels. The optimization utilizes alpha-expansion moves and iterative refinement over a Gaussian pyramid. In this paper we extend the range of applications to image registration. To do this, new data and smoothness terms have to be constructed. We note a great improvement when we measure pixel similarities...
In this study, an image in painting approach using structure-guided priority belief propagation (BP) and label transformations is proposed. The proposed approach contains five stages, namely, Markov random field (MRF) node determination, structure map generation, label set enlargement by label transformations, image in painting by priority-BP optimization, and overlapped region composition. Based...
We describe a method for generating an informative wide-view image using images captured by a moving camera. The generated image allows for events in the scene observed by the camera to be understood easily. Our method does not use 3D shape information explicitly. Instead, it employs the trajectory of feature points across multiple images and generates a composite image by taking into account the...
Cell tissue in microscope images is often grained and its intensities do not well agree with Gaussian distribution assumptions widely used in many segmentation approaches. We present a new cascaded segmentation scheme for inhomogeneous cell tissue based on active contour models. Cell regions are iteratively expanded from initial nuclei regions applying a data-dependent number of optimization levels...
In this paper we present a new image up scaling (single image super resolution) algorithm. It is based on the refinement of a simple pixel decimation followed by an optimization step maximizing the smoothness of the second order derivatives of the image intensity while keeping the sum of the brightness values of each subdivided pixel (i.e. the estimated irradiance on the area) constant. The method...
In this paper, we tackle the problem of image in painting which aims at removing objects from an image or repairing damaged pictures by replacing the missing regions using the information in the rest of the scene. The image in painting method proposed here builds on an exemplar-based perspective so as to improve the local consistency of the in painted region. This is done by selecting the optimal...
In this paper, we propose a novel approach for video stabilization using Markov random field (MRF) modeling and maximum a posteriori (MAP) optimization. We build an MRF model describing a sequence of unstable images and find joint pixel matchings over all image sequences with MAP optimization via Gibbs sampling. The resulting displacements of matched pixels in consecutive frames indicate the camera...
We present a variational approach to obtain a reconstruction of module and phase of a 3D wave field from intensity-only measurements on two or more sensor planes at different axial positions. The objective functional consists of a data fidelity term and a regularizer. The fidelity term corresponds to the likelihood function derived for the Gaussian noisy observations of the wave field intensities...
In this paper, we propose a unified loop filter for high-performance video coding, which suppresses the quantization noise optimally and improves the objective and subjective quality of the reconstructed picture simultaneously. The proposed filter unifies nonlinear enhancement filter (for removing blocking and ringing artifacts) and linear restoration filter (for improving coding efficiency) within...
Modern multimedia workloads provide increased levels of quality and compression efficiency at the expense of substantially increased computational complexity. It is important to leverage the off-the-shelf emerging multi-core processor architectures and exploit all levels of parallelism of such workloads in order to achieve real time functionality at a reasonable cost. This paper presents the implementation,...
A case study describing the influence of TFT LCD graphics on automotive radiated emissions testing and its impact to the FM band receiver. The underlying root-cause of the EMI issue is determined using a novel technique that decodes the display's graphics into the transmitted RGB data and predicts the data's impact to radiated emissions. The countermeasure implemented to resolve the issue is equally...
In this paper, we design and implement 3D scan conversion algorithm using Handel-C language. Primarily we introduce the 3D graphics rendering process and analyze the principle of improved scan conversion algorithm. Then we design and implement the improved scan conversion algorithm. Finally we translate the Handel-C code into Verilog-HDL code and verify the design in ModelSim. Parallel optimization...
This paper proposes an image matching method based on hybrid PSO. The method combines the advantage of the rapid global optimization ability of PSO, and introduces the idea of Population Category Evolution and the mechanism of SA to improve itself. Adopting different evolutionary strategies for different particle categories and making the individual optimal value of the particle accept a lower value...
Significant improvements on the detection of thermal anomalies in multispectral satellite data can be obtained when both the false alarm rate and the probability of detection are known. A desirable, optimum system should have constant false alarm rate and maximum probability of detection. While proper hypotheses can be done on the background statistical distribution, on target for constant false alarm...
This study introduces a parallel implementation of unmixing algorithm for a variable-endmember linear mixture model (VELMM). The model had been developed to retrieve leaf area index (LAI) and fraction of vegetation cover (FVC) from remotely sensed surface reflectance. Since the model consists of a linear sum of two nonlinear functions, the unmixing algorithm involves a constrained optimization process...
In this paper we introduce new model for efficient building extraction and change detection in sparsely populated remotely sensed image pairs. In the two time layers interacting marked point processes recognize the buildings while a priori constraints and low level similarity information are involved in the model. The exploration is accelerated through a non-uniform object birth process, which proposes...
The aim of this paper is the three dimensional reconstruction of urban areas using Very High Resolution (VHR) images. The proposed innovative approach for the three dimensional reconstruction is based on the joint exploitation of both amplitude and interferometric phase images of a multichannel SAR system. The information provided by the amplitude data is added to the 3D reconstruction chain, considering...
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