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  2. scikit-image - Wikipedia

    en.wikipedia.org/wiki/Scikit-image

    scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation , geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection , and more. [ 3 ]

  3. SciPy - Wikipedia

    en.wikipedia.org/wiki/SciPy

    SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

  4. Python Imaging Library - Wikipedia

    en.wikipedia.org/wiki/Python_Imaging_Library

    Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

  6. 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.

  7. Digital image processing - Wikipedia

    en.wikipedia.org/wiki/Digital_image_processing

    The purpose of early image processing was to improve the quality of the image. It was aimed for human beings to improve the visual effect of people. In image processing, the input is a low-quality image, and the output is an image with improved quality. Common image processing include image enhancement, restoration, encoding, and compression.

  8. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and reduce detail.

  9. Image processor - Wikipedia

    en.wikipedia.org/wiki/Image_processor

    Nikon EXPEED, a system on a chip including an image processor, video processor, digital signal processor (DSP) and a 32-bit microcontroller controlling the chip. An image processor, also known as an image processing engine, image processing unit (IPU), or image signal processor (ISP), is a type of media processor or specialized digital signal processor (DSP) used for image processing, in ...