CVDec 2, 2015

Double Sparse Multi-Frame Image Super Resolution

arXiv:1512.00607v12 citations
Originality Incremental advance
AI Analysis

This work addresses multi-frame super-resolution for image processing applications, presenting an incremental improvement over prior methods that handled registration and coding separately.

The paper tackles the problem of multi-frame image super-resolution by jointly optimizing image registration and sparse coding in a single objective function, demonstrating effectiveness through numerical experiments.

A large number of image super resolution algorithms based on the sparse coding are proposed, and some algorithms realize the multi-frame super resolution. In multi-frame super resolution based on the sparse coding, both accurate image registration and sparse coding are required. Previous study on multi-frame super resolution based on sparse coding firstly apply block matching for image registration, followed by sparse coding to enhance the image resolution. In this paper, these two problems are solved by optimizing a single objective function. The results of numerical experiments support the effectiveness of the proposed approch.

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