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        "author": "Daniel Scheffler",
        "author_email": "daniel.scheffler@gfz-potsdam.de",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
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        "description": ".. figure:: http://danschef.gitext.gfz-potsdam.de/arosics/images/arosics_logo.png\n    :target: https://gitext.gfz-potsdam.de/danschef/arosics\n    :align: center\n\n==================================================================================================\nAn Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data\n==================================================================================================\n\n* Free software: GNU General Public License v3\n* **Documentation:** http://danschef.gitext.gfz-potsdam.de/arosics/doc/\n* The (open-access) **paper** corresponding to this software repository can be found here:\n  `Scheffler et al. 2017 <http://www.mdpi.com/2072-4292/9/7/676>`__\n  (cite as: Scheffler D, Hollstein A, Diedrich H, Segl K, Hostert P. AROSICS: An Automated and Robust Open-Source\n  Image Co-Registration Software for Multi-Sensor Satellite Data. Remote Sensing. 2017; 9(7):676).\n* Submit feedback by filing an issue `here <https://gitext.gfz-potsdam.de/danschef/arosics/issues>`__\n  or join our chat here: |Gitter|\n\n.. |Gitter| image:: https://badges.gitter.im/Join%20Chat.svg\n    :target: https://gitter.im/arosics/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link\n    :alt: https://gitter.im/arosics/Lobby?utm_source=share-link&utm_medium=link&utm_campaign=share-link\n\nStatus\n------\n\n.. .. image:: https://img.shields.io/travis/danschef/arosics.svg\n        :target: https://travis-ci.org/danschef/arosics\n\n.. .. image:: https://readthedocs.org/projects/arosics/badge/?version=latest\n        :target: https://arosics.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n.. .. image:: https://pyup.io/repos/github/danschef/arosics/shield.svg\n     :target: https://pyup.io/repos/github/danschef/arosics/\n     :alt: Updates\n\n\n.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/badges/master/build.svg\n        :target: https://gitext.gfz-potsdam.de/danschef/arosics/commits/master\n.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/badges/master/coverage.svg\n        :target: http://danschef.gitext.gfz-potsdam.de/arosics/coverage/\n.. image:: https://img.shields.io/pypi/v/arosics.svg\n        :target: https://pypi.python.org/pypi/arosics\n.. image:: https://img.shields.io/pypi/l/arosics.svg\n        :target: https://gitext.gfz-potsdam.de/danschef/arosics/blob/master/LICENSE\n.. image:: https://img.shields.io/pypi/pyversions/arosics.svg\n        :target: https://img.shields.io/pypi/pyversions/arosics.svg\n\nSee also the latest coverage_ report and the nosetests_ HTML report.\n\nFeature overview\n----------------\n\nAROSICS is a python package to perform **automatic subpixel co-registration** of two satellite image datasets\nbased on an image matching approach working in the frequency domain, combined with a multistage workflow for\neffective detection of false-positives.\n\nIt detects and corrects **local as well as global misregistrations** between two input images in the subpixel scale,\nthat are often present in satellite imagery. The algorithm is robust against the typical difficulties of\nmulti-sensoral/multi-temporal images. Clouds are automatically handled by the implemented outlier detection algorithms.\nThe user may provide user-defined masks to exclude certain image areas from tie point creation. The image overlap area\nis automatically detected. AROSICS supports a wide range of input data formats and can be used from the command\nline (without any Python experience) or as a normal Python package.\n\n\nGlobal co-registration - fast but only for static X/Y-shifts\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nOnly a global X/Y translation is computed within a small subset of the input images (window position is adjustable).\nThis allows very fast co-registration but only corrects for translational (global) X/Y shifts.\nThe calculated subpixel-shifts are (by default) applied to the geocoding information of the output image.\nNo spatial resampling is done automatically as long as both input images have the same projection. However, AROSICS\nalso allows to align the output image to the reference image coordinate grid if needed.\n\nHere is an example of a Landsat-8 / Sentinel-2 image pair before and after co-registration using AROSICS:\n\n.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/raw/master/docs/images/\n           animation_testcase1_zoom_L8_S2_global_coreg_before_after_900x456.gif\n\n\nLocal co-registration - for spatially variable shifts but a bit slower\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nA dense grid of tie points is automatically computed, whereas tie points are subsequently validated using a\nmultistage workflow. Only those tie points not marked as false-positives are used to compute the parameters of an\naffine transformation. Warping of the target image is done using an appropriate resampling technique\n(cubic by default).\n\nHere is an example of the computed shift vectors after filtering false-positives\n(mainly due to clouds in the target image):\n\n.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/raw/master/docs/images/shift_vectors_testcase1__900x824.gif\n\n\nFor further details check out the `documentation <http://danschef.gitext.gfz-potsdam.de/arosics/doc/>`__!\n\nCredits\n-------\n\nAROSICS was developed by Daniel Scheffler (German Research Centre of Geosciences) within the context of the\n`GeoMultiSens <http://www.geomultisens.de/>`__ project funded by the German Federal Ministry of Education and Research\n(project grant code: 01 IS 14 010 A-C).\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\nThe test data represent modified Copernicus Sentinel-2 data (ESA 2016). The input data for the figures in the\ndocumentation have been provided by NASA (Landsat-8) and ESA (Sentinel-2).\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n.. _coverage: http://danschef.gitext.gfz-potsdam.de/arosics/coverage/\n.. _nosetests: http://danschef.gitext.gfz-potsdam.de/arosics/nosetests_reports/nosetests.html\n.. _conda: https://conda.io/docs/\n\n\n\n=======\nHistory\n=======\n\n0.5.0 (2017-09-19)\n------------------\n\nNew features:\n\n* Added two test cases for local co-registration and the respective test data.\n\n* Added test cases for global co-registration\n\n* Added test of output writer and tie point grid visualization.\n\n* Added nosetests. Resolved some setup requirements by conda during test_arosics_install.\n\n* PEP8 code style now checked with automatic style checkers\n\nFixes and improvements:\n\n* Coverage now also working in multiprocessing.\n\n* Replaced test data of test case INTER1 with LZW compressed GeoTIFFs to speed up testing.\n\n* Revised docker container builder.\n\n* Bugfix for unexpected FFTW return value that caused the matching to fail\n\n* Added some docstrings.\n\n* Refactored command line interface 'arosics.py' to 'arosics_cli.py' to fix import issues.\n\n* Added usage documentation for command line interface.\n\n* Removed pykrige from automatically installed libraries during setup. It is now optional (Fixes issue #12)\n\n* Bugfix in connection with optional library pyfftw.\n\n* Revised installation guidelines within README.rst, README.md and installation.rst. Added link for nosetests HTML report.\n\n* Fixed exception in case no arguments are provided to command line interface.\n\n* Revised error handling and added additional check for projection.\n\n* GDAL_DATA environment variable is now handled within py_tools_ds. Updated minimal version of py_tools_ds in setup.py.\n\n* Fixed pickling error when running COREG_LOCAL in multiprocessing under a Windows environment.\n\n* Replaced all occurrences of \"quality grid\" with \"tie point grid\". Updated version info.\n\n\n0.4.0 (2017-07-07)\n------------------\n\nNew features:\n\n* added a logo\n\n* added auto-deploy to PyPI\n\n* added test cases for local co-registration\n\n\nFixes and improvements:\n\n* fixed warping issues in case only very few tie points could be identified\n\n\n0.2.1 (2017-07-03)\n------------------\n\n* First release on PyPI.\n\n\n0.1.0 (2017-06-15)\n------------------\n\n* Package creation.",
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