Introduction

(Click on the image to see it fully)

This is a research blog for CSE 190A. The goal of this quarter-long project is to arrive at an understanding and implementation of multi-view super-resolution that could be of use to Serge Belongie's research group. This project is a follow-up to previous 190A work.

Super-resolution (SR) describes techniques for taking one or more low-quality images of a scene and producing a high-quality image of the same scene. There are at least two general approaches. In the hallucination approach, prior information about what the high-quality image is likely to look like is used to construct a high-quality approximation from a single low-quality image. In the multi-view approach, minimal prior information is assumed, and instead complementary information from multiple photos of the same scene is used to construct a single high-quality photo. Multi-view SR appears to be a well developed field, as I was able to find a number of commercial implementations of multi-view SR, including an iPhone app. From here on, SR will always refer to multi-view SR. My proposal has more details.

The image was taken from S. Farsiu, M. Elad, and P. Milanfar, “A Practical Approach to Super-Resolution”, Invited paper, Proc. of the SPIE Conf. on Visual Communications and Image Processing, San Jose, January 2006.