A learning-based method for image super-resolution from zoomed observations

DSpace/Manakin Repository

A learning-based method for image super-resolution from zoomed observations

Show full item record

Title: A learning-based method for image super-resolution from zoomed observations
Author: CHAUDHURI, SUBHASIS; JOSHI, MV; PANUGANTI, R
Abstract: We propose a technique for super-resolution imaging of a scene from observations at different camera zooms. Given a sequence of images with different zoom factors of a static scene, we obtain a picture of the entire scene at a resolution corresponding to the most zoomed observation. The high-resolution image is modeled through appropriate parameterization, and the parameters are learned from the most zoomed observation. Assuming a homogeneity of the high-resolution field, the learned model is used as a prior while super-resolving the scene. We suggest the use of either a Markov random field (MRF) or an simultaneous autoregressive (SAR) model to parameterize the field based on the computation one can afford. We substantiate the suitability of the proposed method through a large number of experimentations on both simulated and real data.
URI: http://dx.doi.org/10.1109/TSMCB.2005.846647
http://hdl.handle.net/10054/109
http://dspace.library.iitb.ac.in/xmlui/handle/10054/109
Date: 2005


Files in this item

Files Size Format View
30862 2.236Mb Unknown View/Open

This item appears in the following Collection(s)

Show full item record

Search DSpace


Advanced Search

Browse

My Account