Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
In this paper, we propose a new framework for compressive video sensing (CVS) that exploits the inherent spatial and temporal redundancies of a video sequence, effectively. The proposed method splits the video sequence into the key and non-key frames followed by dividing each frame into the small non-overlapping blocks of equal sizes. At the decoder side, the key frames are reconstructed using adaptively...
An optimized iterative algorithm for generalized phase-shifting interferometry is proposed. Using 1/4 plate as phase-shifter, we derive the phase distribution with the initial phase shift of π/2, then a more accurate phase shift can be obtained with the obtained phase distribution. The whole iteration includes the above two steps. The exact phase shift is near π/2, so fewer iterative steps are needed...
The fusion of images captured from multi-modality sensors has been studied for many years. It is aiming at combining multiple sources together to maximize the meaningful information and reduce the redundancy. Meanwhile, sparse representation of images has been attracting more and more attentions. It has been effectively utilized on image reconstruction, image de-noising, super-resolution and others...
It is standard in compressed sensing scenarios to assume that the signal f can be sparsely represented in an orthonormal basis. Whereas, in some sense this isn't very realistic. Indeed, allowing the signal to be sparse with respect to a redundant dictionary adds a lot of flexibility and significantly extends the range of applicability. In this paper, we address the problem of recover signals from...
This paper presents a novel approach for image completion using global optimization, which combines with patch sparsity-based priority and dynamic structural label pruning. In our approach, the completion problem is described by discrete Markov Random Field model with a well defined objective function, and can be solved by adopting belief propagation. Two important extensions are proposed in the paper:...
In this paper, we propose two fast codebook generation techniques with iterative clustering for Vector Quantization (VQ). The techniques proposed in this paper are, Ordered Pairwise Nearest Neighbor (OPNN) and Ordered Pairwise Nearest Neighbor with Multiple Merging (OPNNMM). The conventional PNN technique has been improved using the proposed techniques to reduce the time taken in searching the nearest...
Iterative image reconstruction for positron emission tomography (PET) can improve image quality by using spatial regularization that penalizes image intensity difference between neighboring pixels. The most commonly used quadratic penalty often over-smoothes edges and small objects in reconstructed images. Non-quadratic penalties can preserve edges but may introduce piece-wise constant blocky artifacts...
We present DELTR, an automated pipeline for the analysis of time-resolved light sheet fluorescence microscopy images of zebrafish embryogenesis. It comprises 3D nucleus segmentation using shape-regularized graph cuts, parallelized extraction of geometrical features, and cell tracking by means of combinatorial optimization. We also discuss the interactive visualization software used for validating...
Joint use of partial separability (PS) and spatial-spectral sparsity constraints has previously been demonstrated useful for image reconstruction from undersampled data. This paper extends our early work in this area by proposing a new method for jointly enforcing the PS and spatial total variation (TV) constraints for dynamic MR image reconstruction. An algorithm is also described to solve the underlying...
Bioluminescence imaging (BLI) offers an alternative opportunity for non-invasively visualizing biological processes at the physiological and molecular levels in whole animals. Tomographic bioluminescence imaging (TBI) can further translate planar imaging into three-dimensional quantitative bioluminescent source distribution. Although many reconstruction methods have been developed, efforts are still...
The problem of reconstruction of ultrasound images by means of blind deconvolution has long been recognized as one of the central problems in medical ultrasound imaging. In this paper, a hybrid deconvolution method is employed to recover a reliable estimate of the tissue reflectivity function directly from ultrasound RF data. Here, the “hybridization” suggests a two-stage reconstruction scheme, in...
We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data....
This paper presents a novel approach to simultaneously compute the motion segmentation and the 3D reconstruction of a set of 2D points extracted from an image sequence. Starting from an initial segmentation, our method proposes an iterative procedure that corrects the misclassified points while reconstructing the 3D scene, which is composed of objects that move independently. This optimization procedure...
To improve traffic safety it is important to evaluate the safety of roads and intersections. Today this requires a large amount of manual labor so an automated system using cameras would be very beneficial. We focus on the geometric part of the problem, that is, how to get accurate three-dimensional data from images of a road or an intersection. This is essential in order to correctly identify different...
This paper is concerned with the problem of the two-channel 2-D IIR filter bank design. Using a systematic optimization approach, which is solved in terms of an LMI, the 2-D IIR synthesis filters are designed such that the systems are alias free and then optimized to achieve approximate perfect reconstruction.
Multi-view video plus depth (MVD) data is a set of multiple sequences capturing the same scene at different viewpoints, with their associated per-pixel depth value. Overcoming this large amount of data requires an effective coding framework. Yet, a simple but essential question refers to the means assessing the proposed coding methods. While the challenge in compression is the optimization of the...
The problem of resolution enhancement in images from multiple low-resolution captures has garnered significant attention over the last decade. While initial algorithms estimated the unknown high-resolution (hi-res) image for a fixed set of imaging model parameters, significant recent advances have been in simultaneous maximum aposteriori (MAP) estimation of the hi-res image as well as the geometric...
In this article, we present a new continuous approach based on DC (Difference of Convex functions) programming and DC algorithms (DCA) to the Discrete Tomography. We are concerned with the reconstruction of binary images from their projections in a smaller number of directions. We treat this problem as DC programs. DC programming and DCA, becoming now classic, have been introduced by PHAM DINH T....
The AM-FM Dominant and Channelized Component Analysis (DCA and CCA respectively), consist of applying a filter bank to the Hilbert-tranformed image, and then proceeding with the AM-FM demodulation of each band-pass filtered image. Whereas AM-FM reconstructions based on the CCA use a reasonably small number of locally coherent components, those based on the DCA only use one component: the estimates...
Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. in this paper a new technique is proposed that improves fractal image compression by use of no-search scheme and local search with honey bee mating optimization. This method...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.