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For super resolution (SR) of a 3D scene from multi-view low resolution (LR) images, subpixel registration is one of the main problems due to the difference of the depth for different objects, especially for hand-held uncalibrated cameras. In this paper we proposed a method to solve this problem by estimating the depth map for the LR images and treating the registration as a planar segmentation problem...
In this paper, we propose an improved fast multiple-view image denoising algorithm based on plane sweeping (PS) and non-local means (NLM). Miyata et al. proposed to use PS to convert multi-view images into multi-focus images for noise suppression. It showed improved computational efficiency and comparable denoising quality compared to conventional methods. In this paper, we introduce the notion of...
Web page response time is a key factor to web user satisfaction. Being able to measure or estimate web page response time is important as it allows identification of users facing slow responding web pages. Remedial actions can then be taken to improve response time perceived by these users, which help to enhance satisfaction level of the users towards the web site. In this paper, we present a server-side...
In this paper, we present an automated system for robust biometric recognition based upon sparse representation and dictionary learning. In sparse representation, extracted features from the training data are used to develop a dictionary. Training data of real world applications are likely to be exposed to geometric transformations, which is a big challenge for designing of discriminative dictionaries...
A new Success Estimation Method (SEM) for image unmixing in spatially varying single-path mixing scenarios combining attenuation and spatial distortion, is presented. Staged Sparse Component Analysis is used for estimation of the mixing model and separation of the images. SEM, relying on the assumption of sparseness, inspired by the mask reconstruction method that is used in under-determined systems,...
In this paper, we propose an up-sampling technique in which DCT and Zernike moments (ZMs) are used in hybrid mode to up-sample the images that are down-sampled in DCT domain. DCT-based up-sampling techniques are very effective and simple for up-sampling in DCT domain. However, being discrete and finite, they do not offer any direct way to recover missing details (for instance, substitution of high...
The local ridge orientations are often used to describe fingerprint ridge flow patterns, providing useful information for fingerprint recognition. Although significant advances have been achieved for orientation estimation, it is still challenging to reliably compute the orientations for latent fingerprints, which are usually of poor quality with unclear ridge structure and various overlapping patterns...
High accuracy image registration is critical for the success of multi-frame super-resolution. Conventionally, the shift between images are estimated directly based on the under-sampled low-resolution (LR) image data. However, the high-frequency of LR data is unreliable due to the aliasing effect of sub-sampling, which will deteriorate the accuracy of registration. This paper proposes to resolve the...
Image registration plays an important role in most of multi-frame super-resolution methods. As far as we know, the accuracy of most registration algorithms is not enough for superresolution, which will lead to annoying artifacts. This paper proposes a simple but effective strategy that aims to enhance the performance of existing super-resolution methods. The idea is to measure the reliability of the...
Continuous development, experimentation and validation activities with airborne campaigns pushed towards the proposal of spaceborne missions that could implement SAR Tomography (TomoSAR) on a global scale. Together with innovative SAR imaging modes, TomoSAR plays an essential role in forest mapping for the characterization of 3-D structure and its dynamics at high spatial and temporal resolutions...
Motion estimation for an unknown parameters stereo camera rig is an important topic in the study of computer vision. This paper have proposed a method based on Euclidean reconstruction. Firstly, some feature points are extracted and matched. Then, they are reconstructed into the points in the 3D coordinates up to a scale, which is the length of the baseline. The unknown focal length is the key parameter...
Accurate cell segmentation is an important and long-standing challenge in biomedical image analysis due to large variations in shape and boundary ambiguity. In this paper, we present a segmentation framework for partially overlapping cervical cells. The proposed method starts by cellular clump estimation with morphological reconstruction. Subsequently, the nuclei inside the cellular clumps are located...
Diffusion weighted magnetic resonance imaging(DW-MRI) is used for the quantification of water diffusion with the availability of various tensor based models such as Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI). The increased significance of DKI parameters for the assessment of neurologic diseases as compared to DTI parameters has been shown in several recent studies. Kurtosis...
An obstacle in old document interpretation comes from the lack of image quality. Old documents frequently appear with digitization errors, uneven background, bleed-through effect. A new approach based on morphological color operators to restore the color text is presented. The morphological tools are based on three color spaces, HSI well known in morphological processes, YCrCb and YIQ rarely used...
In the recent years, multi-channel Interferometric SAR (InSAR) techniques have proved to be effective in reconstructing the Digital Elevation Model (DEM) by unwrapping the interferometric phase. Commonly, multi-baseline or multi-frequency configurations are adopted for this aim. In this paper, the possibility of jointly exploiting multi-baseline and multi-frequency approaches for SAR interferometry...
Image-Based Rendering (IBR) algorithms generate high quality photo-realistic imagery without the burden of detailed modeling and expensive realistic rendering. Recent methods have different strengths and weaknesses, depending on 3D reconstruction quality and scene content. Each algorithm operates with a set of hypotheses about the scene and the novel views, resulting in different quality/speed trade-offs...
Modeling the appearance of outdoor scenes from photo collections is challenging because of appearance variation, especially due to illumination. In this paper we present a simple and robust algorithm for estimating illumination properties-shadows and sun direction-from photo collections. These properties are key to a variety of scene modeling applications, including outdoor intrinsic images, realistic...
The use of time-of-flight (TOF) information in positron emission tomography (PET) can significantly improve image quality. Many analytical expressions have been proposed to predict the variance of PET images. However, these methods become impractically time-consuming for TOF-PET. Our work is motivated by the goal of deriving a fast algorithm that can accurately predict image variance of TOF-PET. We...
During the reconstruction process, scatter correction and normalization needs to be applied to correct raw PET data. Normalization corrects for all the variations between the detector responses and typically consists of various components each representing specific physical effect. Only one set of normalization components is typically estimated for the clinical energy window. However, some of the...
Dynamic myocardial perfusion (MP) PET imaging followed by tracer kinetic modeling provides quantitative measurement of myocardial blood flow (MBF). The purpose of this study is to incorporate anatomical information in the 4D direct parametric image reconstruction and to evaluate the performance in detecting regional MBF abnormality. The one-tissue compartment model was formulated in the maximum likelihood...
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