There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

http://ahvazdownload.persiangig.com/document/article/39.pdf

A wavelet tour of signal processing

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

/pdf/computer-vision-algorithms-and-applications-25dn6wu83j.pdf

Computer Vision: Algorithms and Applications

The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, such as curvelets, that first develop a transform in the continuous domain and then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Specifically, we construct a discrete-domain multiresolution and multidirection expansion using nonseparable filter banks, in much the same way that wavelets were derived from filter banks. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and, thus, it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise link between the developed filter bank and the associated continuous-domain contourlet expansion via a directional multiresolution analysis framework. We show that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing applications.

/pdf/the-contourlet-transform-an-efficient-directional-bbl3m3gyb1.pdf

The contourlet transform: an efficient directional multiresolution image representation

In recent years, BitTorrent has emerged as a very popular and scalable peer-to-peer file distribution mechanism. It has been very successful at distributing large files quickly and efficiently without overwhelming the capacity of the origin server, even under extreme flash crowd conditions. In this paper, we present a simulation-based study of BitTorrent. The goal is to deconstruct the BitTorrent system and evaluate the impact of its core mechanisms, both individually and in combination, on overall system performance under a variety of workloads. Our evaluation focuses on several important metrics, including peer link utilization, file download time, and fairness amongst peers in terms of volume of content served. Our results show that BitTorrent performs near-optimally in terms of uplink utilization, download time, and fairness, except under certain extreme conditions. We present and evaluate simple techniques designed to alleviate the suboptimal behavior encountered under such workloads. On the whole, our findings point to the remarkable robustness of BitTorrent’s performance despite (or perhaps due to) the simplicity of its mechanisms.

/pdf/understanding-and-deconstructing-bittorrent-performance-b5qkd302fn.pdf

Understanding and Deconstructing BitTorrent Performance

We present the results of an experiment examining the extent to which individuals will tolerate delays when told that such delays are for security purposes. In our experiment, we asked 800 Amazon Mechanical Turk users to count the total number of times a certain term was repeated in a multipage document. The task was designed to be conducive to cheating. We assigned subjects to eight between-subjects conditions: one of these offered a concrete security reason (virus-scanning) for the delay, another offered only a vague security explanation, while the remaining conditions either offered non-security explanations for the delay or no delay at all—in the case of the control condition. We found that subjects were significantly more likely to cheat or abandon the task when provided with non-security explanations or a vague security explanation for the delay. However, when subjects were provided more explanation about the threat model and the protection ensured by the delay, they were not more likely to cheat than subjects in the control condition who faced no such delay. Our results thus contribute to the nascent literature on soft paternalistic solutions to security and privacy problems by suggesting that, when security mitigations cannot be made “free” for users, designers may incentivize compliant users’ behavior by intentionally drawing attention to the mitigation itself.

Please Continue to Hold: An Empirical Study on User Tolerance of Security Delays.

The present invention provides a large capacity, user defined audio content delivery system. The system delivers uninterrupted music and delivers information content (e.g., news by evaluating and encoding an input audio stream while outputting another stream. Undesirable audio content (e.g., advertisements and unwanted news) are not present in the output audio stream as only desired portions of information content are stored for playback on demand. The invention also includes a user interface that is simple enough to facilitate utilization of the audio system in an automobile and employs standard hardware available in typical computing and/or personal digital assistant equipment. Additionally, the audio system can be portable (e.g., as portable as a personal digital assistant) and can be updated in real time or off line via a personal computer.

Select content audio playback system for automobiles

We examine the problem of how to choose a time-varying filter bank representation for a signal, which is optimal for a rate-distortion cost function. This involves deciding which filter tree to use, (frequency segmentation) and deciding when to prune or add branches to the tree, (time segmentation), For optimality the time and frequency segmentations must be done jointly and not sequentially. Herley et al. (see IEEE Trans. Signal Processing, vol.41, no.12, p.3341-60, 1993) described an algorithm to find the best binary time-frequency split of a signal. In this work, we remove the constraint of binary time segmentation and study the adaptive wavelet packets expansion of a signal with arbitrary segmentation. A fast dynamic programming based algorithm is proposed to solve the optimal segmentation problem. Experimental results on different classes of sources are provided. >

Flexible time segmentations for time-varying wavelet packets

Objects identification in images is generally hard unless the objects are simple geometric shapes such as circles, rectangles, have very particular properties. Even simple geometric shapes can be hard to identify if they deviate even a little from the ideal. We examine the question of identifying and segmenting noisy rectangles, where edges may be ragged, corners may be missing and so on. We test the robustness of our scheme on receipts and small documents obtained from real scans.

Cormac Herley

Papers

Understanding and Deconstructing BitTorrent Performance

Please Continue to Hold: An Empirical Study on User Tolerance of Security Delays.

Select content audio playback system for automobiles

Flexible time segmentations for time-varying wavelet packets

Efficient inscribing of noisy rectangular objects in scanned images