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libvips - A fast image processing library with low memory needs.

  •    C

libvips is a 2D image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolutions, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric formats, from 8-bit int to 128-bit complex. It supports a good range of image formats, including JPEG, TIFF, PNG, WebP, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM, CSV, GIF, Analyze, DeepZoom, and OpenSlide. It can also load images via ImageMagick or GraphicsMagick.

libvips - A fast image processing library with low memory needs.

  •    C

libvips is a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric formats, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good range of image formats, including JPEG, TIFF, PNG, WebP, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. It can also load images via ImageMagick or GraphicsMagick, letting it load formats like DICOM.

miniexr - Small code to write OpenEXR images

  •    C++

Small code to write OpenEXR images

tev - High dynamic range (HDR) image comparison tool for graphics people with an emphasis on OpenEXR images

  •    C++

A high dynamic range (HDR) image comparison tool for graphics people. tev allows viewing images through various tonemapping operators and inspecting the values of individual pixels. Often, it is important to find exact differences between pairs of images. For this purpose, tev allows rapidly switching between opened images and visualizing various error metrics (L1, L2, and relative versions thereof). To avoid clutter, opened images and their layers can be filtered by keywords. A false-color comparison of two multi-layer OpenEXR images of a beach ball. Image courtesy of openexr-images.








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