In a departure from existing approaches, in this article, we propose a novel Enhanced Multiscale Feature Fusion Network (EMFFN). As a deeper and wider network, EMFFN can extract sufficiently multiscale features from the parallel multipath of …

We document a comparison of an acousto-optic tunable filter (AOTF), and a liquid crystal tunable filter (LCTF) based on hyperspectral imaging (HSI). The purpose of this work is to highlight each...

2000年8月23日 · Accomplishing this conversion involves several steps: (1) data-to-signal conversion using the modulation transfer function (MTF) and the Spectral Response of the HSI sensor, (2) removing atmospheric transmittance losses from the HSI data using the MODTRAN code, (3) reintroducing atmospheric transmittance effects for each HSI band over selected ...

2022年12月15日 · 高光谱成像（High Spectral Imaging，HSI）技术是遥感、地球科学、生物医学和材料科学等领域的重要工具，它能够获取多波段的连续光谱信息，提供丰富的光谱和空间特征。

低分辨率高光谱图像（LR-HSI）与高分辨率多光谱图像（HR-MSI）融合技术，广泛用于解决图像空间分辨率与光谱分辨率无法同时保持高水平的矛盾。 从融合效果上分析，现有算法的空间重建误差与光谱重建误差都主要体现在边缘和细节区域。 因此，本文提出了基于细节关注的字典构建和图像重建的融合算法。 在光谱特性保持方面，由于图像邻近效应导致在细节区域光谱分布复杂多样，本文提出对图像层和细节层分别进行字典学习。 在空间特性增强方面，提出了细节感知误 …

A Multistage Information Complementary Fusion Network Based on Flexible-Mixup for HSI-X Image Classification Abstract: Mixup-based data augmentation has been proven to be beneficial to the regularization of models during training, especially in the remote-sensing field where the training data is scarce.

To this end, a novel global–local transformer network (GLT-Net) is proposed for the joint classification of HSI and LiDAR data, in this article. The main idea is to fully exploit the advantage of the convolution operator in characterizing locally correlated features and the promising capability of transformer architecture in learning long ...

Accomplishing this conversion involves several steps: (1) data-to-signal conversion using the modulation transfer function (MTF) and the Spectral Response of the HSI sensor, (2) removing atmospheric transmittance losses from the HSI data using the MODTRAN code, (3) reintroducing atmospheric transmittance effects for each HSI band over selected ...

Accomplishing this conversion involves several steps: (1) data-to-signal conversion using the modulation transfer function (MTF) and the Spectral Response of the HSI sensor, (2) removing atmospheric transmittance losses from the HSI data using the MODTRAN code, (3) reintroducing atmospheric transmittance effects for each HSI band over selected ...

HSI分析主要划分为：降维操作、光谱分解、通道检测分类、用于分类的特征学习、修复和去噪、分辨率提高。 本文研究侧重于HSI分类问题。 列出一个将深度学习使用在HSI分类问题的步骤框架： A.从传统到深度学习模型. HSIC的主要任务----基于光谱或光谱空间属性，给HSI立方体中每一个像素标注。 数学形式为：HSI立方体可以表示为: 这里表示属于类的所有频带，且每个频带包含个样本数量总和，其中是个HSI立方体中的样本，其对应的类别是。 这些手工特征主要用来构建 …