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Generation of super-resolution images from blurred observations using Markov random fields

DSpace at IIT Bombay

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Field Value
 
Title Generation of super-resolution images from blurred observations using Markov random fields
 
Creator RAJAN, D
CHAUDHURI, S
 
Subject superresolution
restoration
 
Description This paper presents a new technique for generating a high resolution image from a blurred image sequence; this is also referred to as super-resolution restoration of images. The image sequence consists of decimated, blurred and noisy versions of the high resolution image. The high resolution image is modeled as a Markov random field (MRF) and a maximum aposteriori (MAP) estimation technique is used. A simple gradient descent method is used to optimize the functional. Further, line fields are introduced in the cost function and optimization using Graduated Non-Convexity (GNC) is shown to yield improved results. Lastly, we present results of optimization using Simulated Annealing (SA).
 
Publisher IEEE
 
Date 2011-10-27T22:17:15Z
2011-12-15T09:12:49Z
2011-10-27T22:17:15Z
2011-12-15T09:12:49Z
2001
 
Type Proceedings Paper
 
Identifier 2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING - VOL IV: SIGNAL PROCESSING FOR COMMUNICATIONS; VOL V: SIGNAL PROCESSING EDUCATION SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO & ELECTROACOUSTICS; VOL VI: SIGNAL PROCESSING THEORY & METHODS STUDENT FORUM,1837-1840
0-7803-7041-4
1520-6149
http://dspace.library.iitb.ac.in/xmlui/handle/10054/16432
http://hdl.handle.net/100/2920
 
Source IEEE International Conference on Acoustics, Speech, and Signal Processing,SALT LAKE CITY, UT,MAY 07-11, 2001
 
Language English