There has been a great deal of material in the area of discrete-time transforms that has been published in recent years. This book does an excellent job of presenting important aspects of such material in a clear manner. The book has 11 chapters and a very useful appendix. Seven of these chapters are essentially devoted to the Fourier series/transform, discrete Fourier transform, fast Fourier transform (FFT), and applications of the FFT in the area of spectral estimation. Chapters 8 through 10 deal with many other discrete-time transforms and algorithms to compute them. Of these transforms, the KarhunenLoeve, the discrete cosine, and the Walsh-Hadamard transform are perhaps the most well-known. A lucid discussion of number theoretic transforms i5 presented in Chapter 11. This reviewer feels that the authors have done a fine job of compiling the pertinent material and presenting it in a concise and clear manner. There are a number of problems at the end of each chapter, an appreciable number of which are challenging. The authors have included a comprehensive set of references at the end of the book. In brief, this book is a valuable contribution to the general areas of signal processing and communications. It can be used for a graduate level course in perhaps two ways. One would be to cover the first seven chapters in great detail. The other would be to cover the whole book by focussing on different topics in a selective manner. This book  by  Elliott  and Rao  is extremely  useful to researchers/engineers who are working  in the areas of signal processing and communications. It i s also an excellent reference book, and hence a valuable addition to one’s library

http://ieeexplore.ieee.org/iel5/5/31347/01457444.pdf

Multirate digital signal processing

Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

/pdf/multiagent-systems-a-modern-approach-to-distributed-5fon0donq1.pdf

Multiagent systems: a modern approach to distributed artificial intelligence

Two-photon microscopy of calcium-dependent sensors has enabled unprecedented recordings from vast populations of neurons. While the sensors and microscopes have matured over several generations of development, computational methods to process the resulting movies remain inefficient and can give results that are hard to interpret. Here we introduce Suite2p: a fast, accurate and complete pipeline that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art method. Its low computational load allows routine detection of ~10,000 cells simultaneously with standard two-photon resonant-scanning microscopes. Recordings at this scale promise to reveal the fine structure of activity in large populations of neurons or large populations of subcellular structures such as synaptic boutons.

/pdf/suite2p-beyond-10-000-neurons-with-standard-two-photon-3042enp0y5.pdf

Suite2p: beyond 10,000 neurons with standard two-photon microscopy

digital video and hdtv algorithms and interfaces is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the digital video and hdtv algorithms and interfaces is universally compatible with any devices to read.

Digital Video And Hdtv Algorithms And Interfaces

Local control strategy for moving-target-enclosing under dynamically changing network topology

The phase correlation method is a well-known image alignment technique with broad applications in medical image processing, image stitching, and computer vision. This method relies on estimating the maximum of the phase-only correlation (POC) function, which is defined as the inverse Fourier transform of the normalized cross-spectrum between two images. The coordinates of the maximum correspond to the translation between the two images. One of the main drawbacks of this method, in its basic form, is that the location of the maximum can only be obtained with integer accuracy. In this paper, we propose a new technique to estimate the location with subpixel accuracy, by minimizing the magnitude of gradient of the POC function around a point near the maximum. We also present some experimental results where the proposed method shows an increased accuracy of at least one order of magnitude with respect to the base method. Finally, we illustrate the application of the proposed algorithm to the rigid registration of digital images.

Phase correlation based image alignment with subpixel accuracy

A network of sensor-based framework for automated visual surveillance

Phase correlation with sub-pixel accuracy

A Comparison of Color Models for Color Face Segmentation

Image fusion refers to the process of integrating complementary image sources from multiple imaging sensor such that the resulting fused image improves the performance of computational analysis tasks such as segmentation, feature extraction and object recognition. The paper introduces a pixel-level image fusion scheme based on linear algebra. The image fusion process begins by computing the discrete wavelet transform of the source images. Then, the wavelet transform of the images are fused using a feature-based rule. A salient feature may extend to several pixels; therefore, a rule that can include a region of pixels containing it results in a more efficient integration. The fusion rule is based on a measurement of the linear dependency of a small window centered on the pixel under consideration. The linear dependency measurement is the Wronskian determinant that is a simple and rigorous test. The performance assessment of the proposed method is established by using mutual information measurement as well as root mean square error and peak signal to noise ratio. The simulation results show that the proposed method is an efficient approach to image fusion.

Ruth M. Aguilar-Ponce

Papers

Phase correlation based image alignment with subpixel accuracy

A network of sensor-based framework for automated visual surveillance

Phase correlation with sub-pixel accuracy

A Comparison of Color Models for Color Face Segmentation

Pixel-Level Image Fusion Scheme based on Linear Algebra