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  2. ImageJ - Wikipedia

    en.wikipedia.org/wiki/ImageJ

    ImageJ is a Java-based image processing program developed at the National Institutes of Health and the Laboratory for Optical and Computational Instrumentation (LOCI, University of Wisconsin). [ 2 ] [ 3 ] Its first version, ImageJ 1.x, is developed in the public domain , while ImageJ2 and the related projects SciJava , ImgLib2 , and SCIFIO are ...

  3. 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 ]

  4. Fiji (software) - Wikipedia

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

    Download as PDF; Printable version; In other projects ... any with Java support: Type: Image processing and Image analysis: License: ... and other advanced image ...

  5. 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.

  6. Gradient-domain image processing - Wikipedia

    en.wikipedia.org/wiki/Gradient-domain_image...

    Alternatively, the pasting can be performed in the gradient domain: if the differences between pixels are pasted rather than the actual pixel values, there is sometimes much less user input needed to achieve a clean result. The following example demonstrates the use of gradient-domain image processing to paste from one image to another seamlessly.

  7. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance.

  8. Kernel (image processing) - Wikipedia

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

    For example, attempting to read a pixel 3 units outside an edge reads one 3 units inside the edge instead. Crop / Avoid overlap Any pixel in the output image which would require values from beyond the edge is skipped. This method can result in the output image being slightly smaller, with the edges having been cropped.

  9. File:Example CNPJ.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Example_CNPJ.pdf

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.