Hyperspectral Simultaneous Anomaly Detection and Denoising: Insights From Integrative Perspective
In data acquisition and transmission, hyperspectral images are inevitably corrupted by additive noises, making it challenging to accurately observe and recognize the materials on the surface of the Earth. However, scholars have been addicted to developing numerous complex methods for separable two-s...
Saved in:
| Main Authors: | Minghua Wang, Lianru Gao, Longfei Ren, Xian Sun, Jocelyn Chanussot |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10621578/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Self-Adaptive Alternating Direction Method of Multipliers for Image Denoising
by: Mingjie Xie, et al.
Published: (2024-11-01) -
A novel n-L1 image restoration approach
by: Lufeng Bai
Published: (2025-02-01) -
Nonlocal and Local Feature-Coupled Self-Supervised Network for Hyperspectral Anomaly Detection
by: Degang Wang, et al.
Published: (2025-01-01) -
An Improvement of the Alternating Direction Method of Multipliers to Solve the Convex Optimization Problem
by: Jingjing Peng, et al.
Published: (2025-02-01) -
Local Sub-Block Contrast and Spatial–Spectral Gradient Feature Fusion for Hyperspectral Anomaly Detection
by: Dong Zhao, et al.
Published: (2025-02-01)