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  2. hqx (algorithm) - Wikipedia

    en.wikipedia.org/wiki/Hqx_(algorithm)

    hqx ("high quality scale") is a set of 3 image upscaling algorithms developed by Maxim Stepin. The algorithms are hq2x , hq3x , and hq4x , which magnify by a factor of 2, 3, and 4 respectively. It was initially created in 2003 for the Super NES emulator ZSNES , [ 1 ] and is used in emulators such as Nestopia , F. CEUX Snes9x., and Snes9x .

  3. 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.

  4. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually results in a visible quality loss. From the standpoint of digital signal processing, the scaling of raster graphics is a two-dimensional example of sample-rate ...

  5. Deep Learning Super Sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    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. Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations ...

  6. waifu2x - Wikipedia

    en.wikipedia.org/wiki/Waifu2x

    waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1] waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). [2] [3] It uses Nvidia CUDA for computing, [4] although alternative implementations that allow for OpenCL [5] and Vulkan [6] have been created.

  7. VIPS (software) - Wikipedia

    en.wikipedia.org/wiki/VIPS_(software)

    Compared to most image processing libraries VIPS needs little RAM and runs quickly, especially on machines with more than one CPU. This is primarily due to its architecture which automatically parallelises the image workflows. [5] The software has two main parts: libvips is the image-processing library and nip2 is the graphical user-interface.

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