Hyperspectral image (HSI) restoration aims at recovering clean images from degraded
observations and plays a vital role in downstream tasks. Existing model-based methods …

Hyperspectral images (HSIs) often suffer from noise arising from both intraimaging
mechanisms and environmental factors. Leveraging domain knowledge specific to HSIs …

Denoising hyperspectral images (HSIs) is a crucial preprocessing procedure due to the
noise originating from intra-imaging mechanisms and environmental factors. Utilizing …

Efficient and precise modeling of the background to accurately identify anomalies is the
cornerstone to hyperspectral anomaly detection. Hyperspectral image (HSI) can be …

Pan-sharpening seeks to generate a high-resolution multi-spectral (HRMS) image by
merging the high-resolution panchromatic (PAN) image and its low-resolution multi-spectral …

Hyperspectral images (HSIs) are inevitably degraded by a mixture of various types of noise,
such as Gaussian noise, impulse noise, stripe noise, and dead pixels, which greatly limits …

Image reconstruction is important for activities that rely on optical and comparative data
analysis. Signals obtained through acquisition systems can be inconsistent due to several …

受成像原理及加工工艺的限制, 非制冷红外探测器存在严重的非均匀性, 为了提升红外成像质量,
必须对图像进行非均匀性校正. 依据成因和分布特点, 该文将红外非均匀性分为低频非均匀性 …

This paper introduces a novel paradigm for hyperspectral image (HSI) denoising, which is
termed\textit {pan-denoising}. In a given scene, panchromatic (PAN) images capture similar …

This paper proposes a novel regularization method, named Spatio-Spectral Structure
Tensor Total Variation (S3TTV), for denoising and destriping of hyperspectral (HS) images …