CompuCorGP

Renowned evolutionary biologist Edward O. Wilson considers the future of biology. Filmmaker Randy Olson discusses the convergence of the science world and Hollywood. They and other scientists, philosophers, and authors come to Arizona State University to celebrate Charles Darwin’s 200th birthday and the 150th anniversary of the publication of On the Origin of Species. Listen. And evolve.

Did you miss any of the trailers that aired during the Super Bowl? Ten in all, they included Angels & Demons, starring Tom Hanks and Ewan McGregor, Land of the Lost, with Will Ferrell, the new Star Trek, a film that brings us back to the very beginning of the enterprise, and the upcoming Up, the highly anticipated movie from Disney Pixar.

“Mac users both new and old should be more than satisfied with” iLife ’09, contends Troy Dreier (laptopmag.com). “New features deliver real value, usually without adding complexity,” he says. “Considering that the improvements to these five apps are numerous, the experience of using them is completely enjoyable, and the price is a modest $79, iLife ’09 easily earns LAPTOP’s Editors’ Choice Award.”

The iPhone is “becoming as handy as stethoscopes in a doctor’s arsenal,” reports Bobby Caina Calvan (seattletimes.com). Take the case of a doctor whose colleague’s niece had been bitten by a dog. The doctor had the girl’s father send a photo of the girl’s wounded eye to his iPhone. “He quickly viewed the injury and issued a soothing diagnosis: No need for an emergency room. Antibiotics, which he prescribed by phone, would do the job.”

When you’re traveling for business, you want to make certain you record all the expenses for which you can be reimbursed. And with XpenseTracker installed on iPhone, you can record those expenses as you incur them. Xpense Tracker provides flexible customization, reporting, and exporting options. It lets you track mileage, set your currency, and use iPhone’s camera to record receipts. There’s even a free lite version available.

“The number of new features in iMovie ’09 is satisfyingly overwhelming,” revels Jeff Carlson (macworld.com) in his 4- (out of 5) mouse review of iMovie ’09. He commends its improved library management, the implementation of image stabilization, and the new Precision Editor. In fact, Carlson asserts that iMovie ’09 has now surpassed earlier versions of iMovie in both features and performance.

Marc Saltzman (usatoday.com) has. And he’s sharing what he’s learned with all of us. Want to know two ways you can save images on iPhone? How “you can delete unwanted emails en masse rather than deleting one at a time”? Or a way to quickly navigate to your Favorite’s screen using the Home button? Saltzman reveals all on his blog.

Spatial resolution of digital images are limited due to optical/sensor blurring and sensor site density. In single-chip digital cameras, the resolution is further degraded because such devices use a color filter array to capture only one spectral component at a pixel location. The process of estimating the missing two color values at each pixel location is known as demosaicking. Demosaicking methods usually exploit the correlation among color channels. When there are multiple images, it is possible not only to have better estimates of the missing color values but also to improve the spatial resolution further (using super-resolution reconstruction). In this paper, we propose a multi-frame spatial resolution enhancement algorithm based on the projections onto convex sets technique.

In super-resolution (SR) reconstruction of images, regularization becomes crucial when insufficient number of measured low-resolution images is supplied. Beyond making the problem algebraically well posed, a properly chosen regularization can direct the solution toward a better quality outcome. Even the extreme case—a SR reconstruction from a single measured image—can be made successful with a well-chosen regularization. Much of the progress made in the past two decades on inverse problems in image processing can be attributed to the advances in forming or choosing the way to practice the regularization. A Bayesian point of view interpret this as a way of including the prior distribution of images, which sheds some light on the complications involved. This paper reviews an emerging powerful family of regularization techniques that is drawing attention in recent years—the example-based approach. We describe how examples can and have been used effectively for regularization of inverse problems, reviewing the main contributions along these lines in the literature, and organizing this information into major trends and directions. A description of the state-of-the-art in this field, along with supporting simulation results on the image scale-up problem are given. This paper concludes with an outline of the outstanding challenges this field faces today.

Accurate registration of images is the most important and challenging aspect of multiframe image restoration problems such as super-resolution. The accuracy of super-resolution algorithms is quite often limited by the ability to register a set of low-resolution images. The main challenge in registering such images is the presence of aliasing. In this paper, we analyse the problem of jointly registering a set of aliased images and its relationship to super-resolution. We describe a statistically optimal approach to multiframe registration which exploits the concept of variable projections to achieve very efficient algorithms. Finally, we demonstrate how the proposed algorithm offers accurate estimation under various conditions when standard approaches fail to provide sufficient accuracy for super-resolution.