The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this work, we use stochastic diffusion equations to improve the reconstruction of binary tomography cross-sections obtained from a small number of projections. A first reconstruction image is obtained with the Total Variation regularization method. The reconstruction is then refined with stochastic approaches. This method is applied to a noisy bone cross-section with 10 projection angles. The main...
This paper addresses the problem of impulse denoising from hyper-spectral images. Impulse noise is sparse; removing impulse noise requires minimizing an l1-norm data fidelity term. Prior studies have exploited the intra-band spatial correlation (leading to sparsity in transform domain) and inter-band spectral-correlation (joint-sparsity) of hyper-spectral images for Gaussian denoising. In this work,...
Oversampled transforms are useful tools for data analysis, since redundancy increases freedom in the choice of the processing. We propose here a framework for oversampled lapped transform of images. More specifically, we establish conditions for perfect reconstruction of 2D data using non-separable windows. We also provide an example of a transform which relies on this approach. We also show the benefit...
The Hit or Miss Transform (HMT) is a well known morphological technique which can be used for shape and object recognition in digital image processing. The standard HMT is a particularly powerful tool for locating objects which are noise free in both the background and foreground regions, do not exhibit internal texture and where objects have well defined edges. Often for various reasons, objects...
In order to overcome the problem of over-segmentation, a novel algorithm of watershed segmentation based on morphological gradient reconstructing is proposed in this paper. In the algorithm, morphological gradient reconstruction is introduced in watershed segmentation, and opening and closing by reconstruction operators are employed to reconstruct gradient image. And then a lot of gradient pixels...
In this paper we consider the problem of motion estimation, analysis and selective reconstruction of objects undergoing rotational motion. There are multiple objects rotating with different angular velocities in the image sequences. The goal is to estimate their distinct motion parameters(in this case is the angular velocities), and also identify their locations at each time instance by selective...
The transformed integral projection method for image alignment of second order radially distorted images is proposed. It is shown that the proposed approach provides a better translation estimation accuracy than the integral projection method and phase correlation methods, especially for noisy distorted images.
This paper proposed a hybrid-cascaded framework for image reconstruction. This framework consists of breaking the reconstruction process into two parts viz. primary and secondary. The primary part consists of simple algebraic iterative technique using Simultaneous Algebraic Reconstruction Technique (SART) for image reconstruction. The task of primary reconstruction will be to provide an enhanced image...
This work presents the conclusions of an experimental study that intends to find the best procedure for reducing the noise of medium resolution infrared images. The goal is to find a good scheme for an image database suitable for use in developing a system to aid breast disease diagnostics. In particular, to use infrared images in the screening and postoperative follow-up in the UFF university hospital,...
In many circumstances the limitation for use of video cameras is energy. The energy needed for compression and transmission of video is substantial, and is linear with the number of transmitted frames. Time-lapse photography, a drastic reduction of transmitted frame rate, is an obvious solution, say by transmitting one frame every several minutes. The temporal resolution of the video is lost. Can...
This paper addresses the issue of magnetic resonance (MR) Image reconstruction at compressive sampling (or compressed sensing) paradigm followed by its segmentation. To improve image reconstruction problem at low measurement space, weighted linear prediction and random noise injection at unobserved space are done first, followed by spatial domain de-noising through adaptive recursive filtering. Reconstructed...
Denoising is important in image processing because degradation by noise affects not only the quality of captured images but also the performance of visual applications that use them. For example, under low light levels, it is difficult to accurately estimate scene depths using noisy stereo images. Conventional methods for denoising find similar regions on an image or among multiple images by block...
Computerized Tomography and Positron Emission Tomography (CT/PET) is an effective and indispensable imaging tool for the application of medical image reconstruction. The noise contained in the data measured by imaging instruments is primarily Poisson type and decreasing the noise has the potential to optimize the quality of CT/PET images. But the traditional iterative reconstruction algorithms of...
In this paper, we propose a two-step approach for the super-resolution reconstruction of video sequences based on the degraded model. Firstly we use the sparse principal component analysis and the linear minimum mean square-error estimation method to remove the noises from the degraded video sequences. Secondly we adopt the Newton-Thiele's vector valued rational interpolation which is one of the nonlinear...
Frequency domain Normalized Convolution (NC) process is widely performed on images to retrieve and extract valuable information in noisy and distorted environment. Genetic Normalized Convolution (GNC) is carried out for features extraction in an image or features reconstructions in a distorted image. In this paper a hybrid approach is adopted where robust algorithm of convolution based on Normalized...
Face recognition using eigenfaces is a popular technique based on principal component analysis (PCA). However, its performance suffers from the presence of outliers due to occlusions and noise often encountered in unconstrained settings. We address this problem by utilizing L1-eigenfaces for robust face recognition. We introduce an effective approach for L1-eigenfaces based on combining fast computation...
Image deblurring is important for photography and biomédical engineering. There are many existing deblurring methods. However, it is still a challenge to reconstruct images clearly without increasing the effect of noise. In this paper, based on that the probability distributions of gradients vary for different parts of an image, we apply edge adaptation and hybrid norm prior and propose a new deblurring...
Based on the least absolute criteria, the image reconstruction problem is transformed into an optimization one by constructing the objective function for optimization. The optimization problem is transformed into the separable optimization problem to be solved by using the alternating direction method. At the same time, a new CT image reconstruction algorithm is got by combining with ART algorithm...
We address the problem of endowing a robot with the capability to learn a repertoire of actions using as little prior knowledge as possible. Taking a handwriting task as an example, we apply the deep learning paradigm to build a network which uses a high-level representation of digits to generate sequences of commands, directly fed to a low-level control loop. Discrete variables are used to discriminate...
In this paper, tracking problem is considered as a sparse approximation of target by templates created during video process. In addition, some trivial templates are used to avoid the effects of noise and illumination changes. Each candidate is sparsely represented by the template set. This goal is achieved by solving an l1- regularized least-square equation. To find tracking result, a candidate with...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.