62 citations · 157 across the 7 of their papers we have counts for
5 papers · 1 filter
Latent Dirichlet Transformer VAE for Hyperspectral Unmixing with Bundled Endmembers
Giancarlo Giannetti, Faisal Z. Qureshi
Hyperspectral images capture rich spectral information that enables per-pixel material identification; however, spectral mixing often obscures pure material signatures. To address…
SpACNN-LDVAE: Spatial Attention Convolutional Latent Dirichlet Variational Autoencoder for Hyperspectral Pixel Unmixing
Soham Chitnis, Kiran Mantripragada, Faisal Z. Qureshi
The hyperspectral pixel unmixing aims to find the underlying materials (endmembers) and their proportions (abundances) in pixels of a hyperspectral image. This work extends the Lat…
Hyperspectral Image Compression Using Implicit Neural Representation
Shima Rezasoltani, Faisal Z. Qureshi
Hyperspectral images, which record the electromagnetic spectrum for a pixel in the image of a scene, often store hundreds of channels per pixel and contain an order of magnitude mo…
Evaluation of Dirichlet Process Gaussian Mixtures for Segmentation on Noisy Hyperspectral Images
Kiran Mantripragada, Faisal Z. Qureshi
Image segmentation is a fundamental step for the interpretation of Remote Sensing Images. Clustering or segmentation methods usually precede the classification task and are used as…
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study
Kiran Mantripragada, Phuong D. Dao, Yuhong He +1
This paper presents a systematic study of the effects of hyperspectral pixel dimensionality reduction on the pixel classification task. We use five dimensionality reduction methods…