Hand Depth Image Denoising and Superresolution via Noise-Aware Dictionaries
This paper proposes a two-stage method for hand depth image denoising and superresolution, using bilateral filters and learned dictionaries via noise-aware orthogonal matching pursuit (NAOMP) based K-SVD. The bilateral filtering phase recovers singular points and removes artifacts on silhouettes by...
Saved in:
Main Authors: | Huayang Li, Dehui Kong, Shaofan Wang, Baocai Yin |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2016-01-01
|
Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/6587162 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Geometry Images for Remeshing
by: Lina Shi, et al.
Published: (2017-01-01) -
Edge and texture aware image denoising using median noise residue U-net with hand-crafted features
by: Soniya S., et al.
Published: (2025-01-01) -
MSLp: Deep Superresolution for Meteorological Satellite Image
by: Liling Zhao, et al.
Published: (2021-01-01) -
Reconstructed Target Range Profile via Unitary ESPRIT Superresolution Algorithm
by: Rui Zhang, et al.
Published: (2017-01-01) -
Improving UAV Aerial Imagery Detection Method via Superresolution Synergy
by: Dianwei Wang, et al.
Published: (2025-01-01)