Image Processing Libraries for Linux

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  • 1

    AlgART Java Libraries

    Open source library for processing arrays and matrices

    AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. Almost all classes and methods are thoroughly documented via JavaDoc (you may read full JavaDoc at the site).
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  • 2
    The CVR-Lib (Computer Vision and Robotics Library) is a C++ object oriented library for computer vision. It provides lots of functionality to solve mathematical problems, many image processing and analysis algorithms, classification tools, and much more.
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  • 3
    CSSgram

    CSSgram

    CSS library for Instagram filters

    Simply put, CSSgram is a library for editing your images with Instagram-like filters directly using CSS. What we're doing is adding filters to the images, as well as applying color and/or gradient overlays via various blending techniques to mimic filter effects. This means less manual image processing and more fun filter effects on the web! We are using pseudo-elements (i.e. :before and :after) to create the filter effects, so you must apply these filters on a containing element (i.e. not a content-block like <img>. The recommendation is to wrap your images in a <figure> tag. If you use custom naming in your CSS architecture, you can add the .scss files for the provided styles within your project and then @extend the filter effects within your style definitions. Mixins allow for multiple filter arguments to be passed into your classes. This is useful for if you want to add filters in addition to the ones provided (i.e. add a blur).
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  • 4
    An image postprocessor for the DIY Book Scanner described on instructables.com and diybookscanner.org. Gets images ready for OCR or for PDF. Written in Java based on a partial port of the Leptonica image processing library.
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  • 5
    The Digital Image Processing Library (dimple) is a C++ class/algorithm library for image processing. Dimple consists of a wide range of image processing routines which can be viewed as low- to mid- level vision tasks.
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  • 6
    Foad (EKG Processing)
    Foad is an open source software which receive an EKG Signal from scanner, WFDB database or heart sensors. Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower the final costs.
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  • 7
    Fourier is a portable image processing and analysis library written in ANSI C. It implements operations such as color space conversions, noise removal, enhancement, morphology, edge detection, thresholding, segmentation, and visual feature extraction
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  • 8
    GENIAL is a C++ library for signal and image processing. It uses template-generic techniques, multi threading, cache optimization and SIMD instructions for Pentium (MMX, SSE, SSE2, SSE3) to achieve high performance: FFT,DCT,Convolution,Linear Algebra...
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  • 9
    Generic Image processing Library of Library (GILL) is a cross-platform and GP-based C++ image processing architecture helping to develop flexible and expandable image processing library.
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  • 10
    Magie is a HDRI (High Dynamic Range Image) and related tasks infrastructure toolkit which is basically focused on the library of the same name. At present Magie contains adaptive DR transformer GIMPs plug-in only.
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  • 11
    IMGH (IMaGe library in C++ Header files) is a simple, light-weight, and cross-platform image processing library, that supports simple editing and drawing, multiple pixel formats (pointers and float). Designed for developers and researchers.
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  • 12
    A set of libraries which includes: - Time schedule library - HTTP communication library - Generic parser library - Image processing library
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  • 13
    ImLib3D is a C++ library and visualisation system for 3D image processing. It contains most basic image processing algorithms, and some more sophisticated ones. ImLib3D images are STL-compliant templated containers. Keywords: Medical, MRI, Brain
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  • 14
    The Image Processing Library 98 (IPL98) is a platform independent image C/C++ library. IPL98 is useful, for combining tailor-made image processing and interpretation with standard methods for acquisitions, processing, and storage of image information.
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  • 15
    This is a small Java based library and a software developed on NetBeans for the studying purposes of CS students who are doing image processing. -sasi
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  • 16
    This project aims at implementing a variety of the image processing algorithms by means of GIL.
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  • 17
    ImageSharp

    ImageSharp

    A modern, cross-platform, 2D Graphics library for .NET

    ImageSharp carries no native dependencies and can be installed anywhere that supports .NET Standard 2.0+, ImageSharp can be used in device, cloud, and embedded/IoT scenarios. ImageSharp's API is unparalleled for it's ease of use. Designed from the ground up to be flexible and extensible, the library provides API endpoints for common image processing operations and the building blocks to allow for the development of additional operations. Complete support for jpeg, bmp, gif, pbm, png, tga, tiff, and webp with more formats on the way. Supports over 25 different pixel formats. Metadata editing support (IPTC EXIF). Colorspace transforms (RGB/CMYK/Grayscale/CIELab and many more). Over 40 common processing operations. Great performance and memory friendly; work with any dimensions (even hundreds of megapixels). ImageSharp is brimming with features. Common operations are only a few keystrokes away.
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  • 18
    A very basic library with image processing functions.
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  • 19
    JIPL (Java Image Processing Library) is an attempt to provide an efficient way to load, filter, manipulate, and save images. The goal is to provide an intuitive and extensible library.
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  • 20
    JPedal JBIG2 Image Decoder

    JPedal JBIG2 Image Decoder

    A JBIG2 decoder written for Java under a BSD license

    The JPedal JBIG2 Image Decoder is a 100% pure Java image decoder for the JBIG2 file format. The decoder takes the JBIG2 image processing technology developed for the JPedal PDF renderer in 2007 and makes it available as a generic library for more general usage. The JDeli Image Library https://www.idrsolutions.com/jdeli contains a much enhanced and faster version and also provides a complete ImageIO replacement (see https://www.idrsolutions.com/jdeli/imageio-replacement) for Tiff, JPEG, JPEG2000, Png as well as lots of other image formats including Dicom, WMF, PSD, SGI and WebP.
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  • 21
    JaToo Imager

    JaToo Imager

    View and alter images (batch processing available).

    JaToo Imager is a Java Open Source application created to view and alter images. Batch processing is also provided.
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  • 22
    The Java Vision Toolkit (JVT) is a Java Advanced Imaging GUI/library for machine vision and image processing applications. It provides a framework for machine vision and image processing algorithms for 2D and 3D images.
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  • 23
    Kornia

    Kornia

    Open Source Differentiable Computer Vision Library

    Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs.
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  • 24
    robust image processing library
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  • 25
    Grayscale and binary image processing library for Qt.
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