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Images can often be improved – or even transformed – by using graphics software such as Photoshop or the free GIMP and Paint.NET applications. Many other programs also have photo-enhancing tools, including facilities for semi-automatic image enhancement, so that you need only click a button, or choose a thumbnail, to have a positive effect on image quality.
The basic concept underlying the various resolution enhancement systems is the creative use of diffraction in certain locations to offset the diffraction in others. For instance, when light diffracts around a line on the mask it will produce a series of bright and dark lines, or "bands". that will spread out the desired sharp pattern.
Super-resolution imaging (SR) is a class of techniques that improve the resolution of an imaging system. In optical SR the diffraction limit of systems is transcended, while in geometrical SR the resolution of digital imaging sensors is enhanced.
The first step is an image enhancement network which uses the current frame and motion vectors to perform edge enhancement, and spatial anti-aliasing. The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution.
An image scaled with nearest-neighbor scaling (left) and 2×SaI scaling (right) In computer graphics and digital imaging, image scaling refers to the resizing of a digital image. In video technology, the magnification of digital material is known as upscaling or resolution enhancement.
Then the resolution-independent version is rendered as a raster image at the desired resolution. This technique is used by Adobe Illustrator Live Trace, Inkscape, and several recent papers. [6] Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity.
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