TPPI-Net: Towards Efficient and Practical Hyperspectral Image Classification

03/18/2021
by   Hao Chen, et al.
0

Hyperspectral Image(HSI) classification is the most vibrant field of research in the hyperspectral community, which aims to assign each pixel in the image to one certain category based on its spectral-spatial characteristics. Recently, some spectral-spatial-feature based DCNNs have been proposed and demonstrated remarkable classification performance. When facing a real HSI, however, these Networks have to deal with the pixels in the image one by one. The pixel-wise processing strategy is inefficient since there are numerous repeated calculations between adjacent pixels. In this paper, firstly, a brand new Network design mechanism TPPI (training based on pixel and prediction based on image) is proposed for HSI classification, which makes it possible to provide efficient and practical HSI classification with the restrictive conditions attached to the hyperspectral dataset. And then, according to the TPPI mechanism, TPPI-Net is derived based on the state of the art networks for HSI classification. Experimental results show that the proposed TPPI-Net can not only obtain high classification accuracy equivalent to the state of the art networks for HSI classification, but also greatly reduce the computational complexity of hyperspectral image prediction.

READ FULL TEXT
04/16/2019

Deep Neural Network Based Hyperspectral Pixel Classification With Factorized Spectral-Spatial Feature Representation

Deep learning has been widely used for hyperspectral pixel classificatio...
04/21/2022

GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification

Hyperspectral image (HSI) classification is the most vibrant area of res...
08/02/2015

On Hyperspectral Classification in the Compressed Domain

In this paper, we study the problem of hyperspectral pixel classificatio...
06/09/2019

Pixel DAG-Recurrent Neural Network for Spectral-Spatial Hyperspectral Image Classification

Exploiting rich spatial and spectral features contributes to improve the...
05/17/2020

Hyperspectral Image Classification Based on Sparse Modeling of Spectral Blocks

Hyperspectral images provide abundant spatial and spectral information t...
04/01/2021

A study on the effects of compression on hyperspectral image classification

This paper presents a systematic study the effects of compression on hyp...
08/04/2020

Hyperspectral Image Classification with Spatial Consistence Using Fully Convolutional Spatial Propagation Network

In recent years, deep convolutional neural networks (CNNs) have shown im...