JOURNAL ARTICLE

Wavelet based nonlocal-means super-resolution for video sequences

Abstract

Video sequence resolution enhancement became a popular research area during the last two decades. Although traditional super-resolution techniques have been successful in dealing with image sequences, many constraints such as global translation between frames, have to be imposed to obtain good performance. In this paper, we present a new wavelet-based nonlocal-means (WNLM) framework to bypass the motion estimation stage. It can handle complex motion changes between frames. Compared with the nonlocal-means (NLM) super-resolution framework, the proposed method provides better result in terms of PSNR and faster processing.

Keywords:
Computer science Wavelet Artificial intelligence Computer vision Sequence (biology) Superresolution Motion estimation Wavelet transform Resolution (logic) Translation (biology) Image resolution Motion (physics) Image (mathematics) Pattern recognition (psychology) Algorithm

Metrics

24
Cited By
1.92
FWCI (Field Weighted Citation Impact)
12
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology

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