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9-slice scaling (also known as Scale 9 grid, 9-slicing or 9-patch) is a 2D image resizing technique to proportionally scale an image by splitting it in a grid of nine parts. [1] The key idea is to prevent image scaling distortion by protecting the pixels defined in 4 parts (corners) of the image and scaling or repeating the pixels in the other ...
The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.
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.
Next, the rotated image is created with a nearest-neighbor scaling and rotation algorithm that simultaneously shrinks the big image back to its original size and rotates the image. Finally, overlooked single-pixel details are (optionally) restored if the corresponding pixel in the source image is different and the destination pixel has three ...
To view multiple windows in AOL Desktop Gold, you'll want to resize and position them appropriately on your screen. You can also save the window size and position for the next time you sign in to Desktop Gold. Open the window you want to resize or move. Click and drag the outside border of the window to modify its size.
In the program, layers can be stacked, merged, or defined when creating a digital image. Layers can be partially obscured allowing portions of images within a layer to be hidden or shown in a translucent manner within another image. Layers can also be used to combine two or more images into a single digital image. For the purpose of editing ...
The result of applying several of these modes depends linearly on the pixel level of the top layer. In such cases, when the top layer is purely black, one gets a certain transformation of the bottom layer (which may be just a purely black or purely white image). When the top layer is purely white, one gets another such transformation.
A Laplacian pyramid is very similar to a Gaussian pyramid but saves the difference image of the blurred versions between each levels. Only the smallest level is not a difference image to enable reconstruction of the high resolution image using the difference images on higher levels. This technique can be used in image compression. [13]