JOURNAL ARTICLE

Nonlocal based Super Resolution with rotation invariance and search window relocation

Abstract

In this paper, we present a novel method for Super Resolution (SR) reconstruction with rotation invariance and search window relocation. To combine complementary information in observed images to generate a higher resolution image, we first relocate search window to involve potential similar patches and then use rotation invariance similarity measure to find accurate similar patches. Comparing with Nonlocal Means SR, our algorithm can find more similar patches for weighted average. Experimental results demonstrate superior performance of the proposed method in terms of both objective measurements and subjective evaluation.

Keywords:
Rotation (mathematics) Relocation Window (computing) Similarity (geometry) Artificial intelligence Resolution (logic) Computer science Algorithm Pattern recognition (psychology) Measure (data warehouse) Image (mathematics) Computer vision Mathematics Data mining

Metrics

9
Cited By
4.00
FWCI (Field Weighted Citation Impact)
7
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
© 2026 ScienceGate Book Chapters — All rights reserved.