12937715
Improvement of Color Video Demosaicking in Temporal Domain
Color demosaicking is critical to the image quality of digital still and video cameras that use a single-sensor array. Limited by the mosaic sampling pattern of the color filter array (CFA), color artifacts may occur in a demosaicked image in areas of high-frequency and/or sharp color transition structures. However, a color digital video camera captures a sequence of mosaic images and the temporal dimension of the color signals provides a rich source of information about the scene via camera and object motions. This paper proposes an inter-frame demosaicking approach to take advantage of all three forms of pixel correlations: spatial, spectral, and temporal. By motion estimation and statistical data fusion between adjacent mosaic frames, the new approach can remove much of the color artifacts that survive intra-frame demosaicking and also improve tone reproduction accuracy. Empirical results show that the proposed inter-frame demosaicking approach consistently outperforms its intra-frame counterparts both in peak signal-to-noise measure and subjective visual quality
9760560
An edge-guided image interpolation algorithm via directional filtering and data fusion
Preserving edge structures is a challenge to image interpolation algorithms that reconstruct a high-resolution image from a low-resolution counterpart. We propose a new edge-guided nonlinear interpolation technique through directional filtering and data fusion. For a pixel to be interpolated, two observation sets are defined in two orthogonal directions, and each set produces an estimate of the pixel value. These directional estimates, modeled as different noisy measurements of the missing pixel are fused by the linear minimum mean square-error estimation (LMMSE) technique into a more robust estimate, using the statistics of the two observation sets. We also present a simplified version of the LMMSE-based interpolation algorithm to reduce computational cost without sacrificing much the interpolation performance. Experiments show that the new interpolation techniques can preserve edge sharpness and reduce ringing artifacts
7762229
Edge detection by scale multiplication in wavelet domain
This paper proposes a wavelet based edge detection scheme by scale multiplication. The dyadic wavelet transforms at two adjacent scales are multiplied as a product function to magnify the edge structures and suppress the noise. Unlike many multiscale techniques that first form the edge maps at several scales and then synthesize them together, we determined the edges as the local maxima directly in the scale product after an efficient thrsholding. It is shown that the scale multiplication achieves better results than either of the two scales, especially on the localization performance. The dislocation of neighboring edges is also improved when the width of detection filter is set large to smooth noise. Experiments on natural images are compared with the Laplacian of Gaussian and Canny edge detection algorithms.
548723
Noise Reduction for Magnetic Resonance Images via Adaptive Multiscale Products Thresholding
Edge-preserving denoising is of great interest in medical image processing. This paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. A Canny edge detector-like dyadic wavelet transform is employed. This results in the significant features in images evolving with high magnitude across wavelet scales, while noise decays rapidly. To exploit the wavelet interscale dependencies we multiply the adjacent wavelet subbands to enhance edge structures while weakening noise. In the multiscale products, edges can be effectively distinguished from noise. Thereafter, an adaptive threshold is calculated and imposed on the products, instead of on the wavelet coefficients, to identify important features. Experiments show that the proposed scheme better suppresses noise and preserves edges than other wavelet-thresholding denoising methods.
1918361
Canny edge detection enhancement by scale multiplication
The technique of scale multiplication is analyzed in the framework of Canny edge detection. A scale multiplication function is defined as the product of the responses of the detection filter at two scales. Edge maps are constructed as the local maxima by thresholding the scale multiplication results. The detection and localization criteria of the scale multiplication are derived. At a small loss in the detection criterion, the localization criterion can be much improved by scale multiplication. The product of the two criteria for scale multiplication is greater than that for a single scale, which leads to better edge detection performance. Experimental results are presented.
11724747
Wavelet estimation of fractional Brownian motion embedded in a noisy environment
This correspondence proposes a wavelet-based fractional Brownian motion (fBm) signal estimation scheme. Despite the fact that wavelet transform approximately whitens the fBm processes, it is observed that statistical dependencies still exist across adjacent wavelet scales and between neighboring wavelet coefficients. These dependencies can be exploited to improve the estimation of fBm signals embedded into noise. The idea is to reorganize the wavelet coefficients into a scale-time mixture model and then carry out the minimum mean-square-error estimation (MMSE) using the model. Experiments show that the proposed scheme obtains better estimates than Wornell and Oppenheim's algorithm, in which the wavelet dependencies are not utilized.
214819
Scalable search-based image annotation of personal images
With the prevalence of digital cameras, more and more people have considerable digital images on their personal devices. As a result, there are increasing needs to effectively search these personal images. Automatic image annotation may serve the goal, for the annotated keywords could facilitate the search processes. Although many image annotation methods have been proposed in recent years, their effectiveness on arbitrary personal images is constrained by their limited scalability, i.e. limited lexicon of small-scale training set. To be scalable, we propose a search-based image annotation (SBIA) algorithm that is analogous to Web page search. First, content-based image retrieval (CBIR) technology is used to retrieve a set of visually similar images from a large-scale Web image set. Then, a text-based keyword search (TBKS) technique is used to obtain a ranked list of candidate annotations for each retrieved image. Finally, a fusion algorithm is used to combine the ranked lists into the final annotation list. The application of both efficient search technologies and Web-scale image set guarantees the scalability of the proposed algorithm. Experimental results on U. Washington dataset show not only the effectiveness and efficiency of the proposed algorithm but also the advantage of image retrieval using annotation results over that using visual features.
887255
An automated design tool for analog layouts
In this paper, a layout synthesis tool for the design of analog integrated circuits (ICs) is presented. This tool offers great flexibility that allows analog circuit designers to bring their special design knowledge and experiences into the synthesis process to create high-quality analog circuit layouts. Different from conventional layout systems that are limited to the optimization of single devices, our layout generation tool attempts to optimize more complex modules. This tool includes a complete tool suite that covers the following three major analog physical designs stages. 1) Module Generation: designers can develop and maintain their own technology- and application-independent module generators for subcircuits using an in-house developed description language. 2) Placement: a two-stage placement technique, tailored for the analog placement design, is proposed. In particular, this placement algorithm features a novel genetic placement stage followed by a fast simulated reannealing scheme. 3) Routing: the minimum-Steiner-tree-based global routing is developed, and it is actually integrated into the placement procedure to improve reliability and routability of the placement solutions. Following the global routing, a compaction-based constructive detailed routing finally completes the interconnection of the entire layout. Several testing circuits have been applied to demonstrate the design efficiency and the effectiveness of this tool. Experimental results show that this new layout tool is capable of producing high quality layouts comparable to those manually done by layout experts but with much less design time
1125168
Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations
Strong and weak simulation relations have been proposed for Markov chains,
while strong simulation and strong probabilistic simulation relations have been
proposed for probabilistic automata. However, decision algorithms for strong
and weak simulation over Markov chains, and for strong simulation over
probabilistic automata are not efficient, which makes it as yet unclear whether
they can be used as effectively as their non-probabilistic counterparts. This
paper presents drastically improved algorithms to decide whether some
(discrete- or continuous-time) Markov chain strongly or weakly simulates
another, or whether a probabilistic automaton strongly simulates another. The
key innovation is the use of parametric maximum flow techniques to amortize
computations. We also present a novel algorithm for deciding strong
probabilistic simulation preorders on probabilistic automata, which has
polynomial complexity via a reduction to an LP problem. When extending the
algorithms for probabilistic automata to their continuous-time counterpart, we
retain the same complexity for both strong and strong probabilistic
simulations.
7408744
Projection defocus analysis for scene capture and image display
In order to produce bright images, projectors have large apertures and hence narrow depths of field. In this paper, we present methods for robust scene capture and enhanced image display based on projection defocus analysis. We model a projector's defocus using a linear system. This model is used to develop a novel temporal defocus analysis method to recover depth at each camera pixel by estimating the parameters of its projection defocus kemel in frequency domain. Compared to most depth recovery methods, our approach is more accurate near depth discontinuities. Furthermore, by using a coaxial projector-camera system, we ensure that depth is computed at all camera pixels, without any missing parts. We show that the recovered scene geometry can be used for refocus synthesis and for depth-based image composition. Using the same projector defocus model and estimation technique, we also propose a defocus compensation method that filters a projection image in a spatially-varying, depth-dependent manner to minimize its defocus blur after it is projected onto the scene. This method effectively increases the depth of field of a projector without modifying its optics. Finally, we present an algorithm that exploits projector defocus to reduce the strong pixelation artifacts produced by digital projectors, while preserving the quality of the projected image. We have experimentally verified each of our methods using real scenes.
3761715
A multicommodity flow model for distributed stream processing
The rapid development of computer technology has enabled streaming applications to emerge from many areas of the IT industry. A fundamental problem in such stream processing systems is how to best utilize the available resources so that the overall system performance is optimized. In most real time systems, applications are often running in a decentralized, distributed environment. At any given time, no server has the global information about all the servers in the system. It is thus desirable to have distributed solutions capable of adapting to or absorbing local changes in production rates and in network conditions. This paper addresses the fundamental resource allocation question in the distributed stream processing setting. Specifically, we consider a generic model for stream processing systems. Each stream is required to complete a series of tasks to become finished product. Each server is responsible for a subset of the processing tasks for possibly a subset of the streams. All servers have finite computing resources and all communication links have finite available bandwidth. We consider the resource allocation problem so as to maximize the total throughput of the system. Our problem can be described as a generalization of the traditional multicommodity flow problem [1]. Traditional multicommodity flow problem looks for the best way to use of the link capacities to deliver the maximum throughput for the flows in the whole network. In our problem, in addition to the link bandwidth constraints, we also have processing power constraints for each server. Furthermore, we allow flow shrinkage or expansion so as to model operations such