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  2. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    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.

  3. Morphing - Wikipedia

    en.wikipedia.org/wiki/Morphing

    Long before digital morphing, several techniques were used for similar image transformations. Some of those techniques are closer to a matched dissolve - a gradual change between two pictures without warping the shapes in the images - while others did change the shapes in between the start and end phases of the transformation.

  4. Blend modes - Wikipedia

    en.wikipedia.org/wiki/Blend_modes

    Dodge and burn change the lightness of the pictures, inspired by the dodging and burning performed in a darkroom. Dodging lightens an image, while burning darkens it. Dodging the image is the same as burning its negative (and vice versa). Dodge modes: The Screen blend mode inverts both layers, multiplies them, and then inverts that result.

  5. Lenticular printing - Wikipedia

    en.wikipedia.org/wiki/Lenticular_printing

    This can be used to create an image that moves ("motion effect"), or can create a "zoom" or "morph" effect, in which part of the image expands in size or changes shape as the angle of view changes. The movie poster of the film Species II is an example of this technique.

  6. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    The Image Size dialog can be used as an image calculator of sorts. For example, a 1600 × 1200 image with a resolution of 200 ppi will produce a printed image of 8 × 6 inches. The same image with 400 ppi will produce a printed image of 4 × 3 inches. Change the resolution to 800 ppi, and the same image now prints out at 2 × 1.5 inches.

  7. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.

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