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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Tricia Mayer</author_name><author_url>https://www.microsoft.com/en-us/research/people/tmayer/</author_url><title>Functional Images - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="5rPtQo8dP8"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/functional-images/"&gt;Functional Images&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/functional-images/embed/#?secret=5rPtQo8dP8" width="600" height="338" title="&#x201C;Functional Images&#x201D; &#x2014; Microsoft Research" data-secret="5rPtQo8dP8" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>There have been many libraries for generating images using functional programming, each based on its own fixed set of geometric primitives and combinators. In contrast, this paper addresses the general notion of images, based on a very simple model: functions over continuous 2D space. Spatial transforms are mappings from 2D space to itself, and regions [&hellip;]</description></oembed>
