Ulead PhotoImpact 10 Professional Image Editing Made Easy Features

Ulead® PhotoImpact® 10 is a complete image-editing suite for enthusiasts who want inspiring results, without the steep learning curve. Basic Mode offers users new to digital photography a streamlined interface for most common tasks. Advanced users can take advantage of a complete set of high-end tools for retouching, montages, painting, drawing and Web graphics. PhotoImpact 10 makes it easy to achieve professional results with your photos.

Ulead® PhotoImpact® 10 Easy to Learn & Use
• Welcome Screen – A great way to get started immediately. Choose between Create New Image, Browse Images, Download Images, Scan Images, Fix Photos, Watch Tutorial and Help.
• Basic Mode – A simple and intuitive interface that has just the right tools for common image editing tasks – ideal for those new to PhotoImpact or digital photography. Easily toggle between Basic Mode and Standard Mode for the complete advanced tool set.
• User Interface* – Revamped with clearer icons, reorganized menu bar, enlargeable effects window, Windows® address bar style browser, updated Layer Manager, more natural flowing painting tools and other usability enhancements.
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• Dockable Panels – Increase your productivity by locking frequently used panels and toolbars together for complete control over your workspace.
• Large Photo Handling* - Enhanced performance for large photos with features such as Color Replacement, Hue and Saturation, Artistic Effects, Gaussian Blur, and Unsharp Mask.
• Batch Convert – Increase your productivity by converting the file format, data type and resolution of multiple images in just one click.
• Quick Command Panel – Save time by recording macros to perform a set of tasks on any group of images. Enhanced with even more recordable actions.
• EasyPalette TM– Now reorganized for increased ease of use and the ability to save macros. Visually choose the effects and attributes you apply from a panel of thumbnails – just drag-and-drop any effect on to an image, selected area or object for the most intuitive way to apply effects.
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• Split View – A new single-image mode for faster previewing and increased productivity.
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• UFO Preview – View PhotoImpact vector graphics files directly in Windows® Explorer – so you’ll know exactly which files you want to open.
• Undo Levels – Backtrack up to the last 200 actions performed, so you’ll have plenty of room for creative experimentation without worrying about losing your original project.

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Performance Characterization in Computer Vision A Tutorial

The discipline variously known as Computer Vision, Machine Vision and Image Analysis has its origins in the early artificial intelligence research of the late 1950s and early 1960s. Hence, roughly two generations of researchers have pitted their wits against the problem. The pioneers of the first generation worked with computers that were barely capable of handling image data — processing had to be done line-by-line from backing store — and programs almost always had to be run as batch jobs, ruling out any form of interaction. Even capturing digital images was an impressive feat. Under such difficult conditions, the techniques that were developed were inevitably based on the mathematics of image formation and exploited the values of pixels in neighbouring regions. Implementing them was a non-trivial task, so much so that pretty well any result was an impressive achievement.

The second generation of researchers coincided with the birth of the workstation. At last, an individual researcher could process images online, display them, and interact with them. These extra capabilities allowed researchers to develop algorithms that involved significant amounts of processing. A major characteristic of many algorithms developed during this second generation was the quest for optimality. By formulating and manipulating a set of equations that described the nature of the problem, a solution can usually be obtained by a least-squares method which, of course, is in some sense optimal. Consequently, any number of techniques appeared with this ‘optimality’ tag. Sadly, none of these papers were able to provide credible experimental evidence that the results from the optimal technique was significantly better than existing (presumably sub-optimal) ones.

We are now in the early years of the third generation. Computers, even PCs, are so fast and so well-endowed with storage that it is entirely feasible to process large datasets of images in a reasonable time — and this means it is possible to quantify the performance of an algorithm. As a result, the vision community has finally started to turn its attention to issues related to testing and comparing algorithms: performance assessment. The most visible (no pun intended) aspect of this is the competitions that are often organized in association with major vision conferences. These essentially ask the question “which algorithm is best?” Although a natural enough question to ask, it lacks subtlety and is potentially rather dangerous: if the community as a whole adopts an algorithm as “the standard” and concentrates on improving it further, that action can stifle research into other algorithms.

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