Work done as part of the CS 192-26 at UCB
How does your phone make panoramas? How does sharpening work on photoshop? How can you intelligently use the data encoded in images to enhance what our eye sees? In this series of projects supplied by the department, I worked through some of the fundamentals of computational imaging. Some of these ideas have been around longer than color cameras, and others use the cutting edge of the computer science field.
These projects, as posted here, are somewhat rough, as I attempted this class during a particularly harrowing semester. I've posted them here, however, so that what I did accomplish gets a platform, and so I have a place to put updates when I return to this code.
In this warm-up project, we take black and white photos, taken with three color filters, and combine them to get color images in a time where there were no color cameras. Though the results are beautiful color images, this project is specially focused on image alignment tactics.
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In this project, we look at the filters and frequencies that make up spatial information. We can use this information to blend images together, like the infamous orapple.
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One of my favorite projects, face morphing allows us to use key points in facial structures to translate the color references onto a different structure. I demonstrate this with mine and my brothers faces.
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This project expands the idea of image morphing to identifying key features between photos. With this we can flatten a wall, or stitch photos together as in a panorama.
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A follow up to the face morph project, this looked at using neural nets, trained on the danish faces, to identify key features in the pictures we wanted to morph to.
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This was two pre-canned projects focusing on tiling and dynamic range. The tiling problem is actually quite interesting for low storage graphics.
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