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And what weamp;#39;re going to do, actually, is do clustering twice. The first thing we do is, weamp;#39;re going to cluster in that big feature space I was just showing you. And those clusters are going to be referred to as textons. Now this is a word, I think itamp;#39;s a word that was coined by Bela Julesz who was a psychophysicist, guy who did random autostereograms quite a while ago. And they were referring to things like T-junctions and little end-stops and other textural descriptors that ex, existed in, in images as sort of he saw them. And the idea is that these clusters in the feature space would be different little textural elements that were found in these images, right? And so you would describe each little window, okay, by whatamp;#39;s referred to as its texton histogram. Thatamp;#39;s what this thing is going to be showing here. Weamp;#39;ll, weamp;#39;ll take a little bit more of that. But the idea is that, here there is just a single value at every pixel, which
