Super resolution reconstruction on different sets of low resolution measurements

Author

al-Rahman, Sahar A.

Source

المؤتمر الدولي الهندسي الرابع : “نحو هندسة القرن الحادي و العشرين” : الذي نظمته كلية الهندسة بالجامعة الإسلامية-غزة يومي الاثنين و الثلاثاء الخامس عشر و السادس عشر من تشرين أول / أكتوبر 2012.

Publisher

Islamic University of Gaza Faculty of Engineering

Publication Date

2012-10-31

Country of Publication

Palestine (Gaza Strip)

No. of Pages

10

Main Subjects

Engineering & Technology Sciences (Multidisciplinary)

English Abstract

This paper deals with the problem of reconstructing High Resolution (HR) still image from a set of displaced, under sampled, and blurred measured images.

It proposes an algorithm that uses the affine block-based algorithm in the maximum likelihood estimator.

It is tested using synthetic grayscale and mono color images, where the reconstructed image can be compared with its original.

A number of experiments were performed with the proposed algorithm over different sets of low resolution (LR) images to evaluate its behavior as a function of the number of available LR images.

All the simulations correspond to synthetic data, in order to bypass problems such as translation estimation between measurements, and the blurring function estimation.

The proposed algorithm accurately recovers the HR image even in the case where just very few input images are provided.

Data Type

Conference Papers

Record ID

BIM-777223

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