Spectroscopy and Spectral Analysis, Volume. 44, Issue 3, 872(2024)

Residual Quantization of Radiation Depth in Hyperspectral Image and Its Influence on Terrain Classification

WANG Juan1,2,3, ZHANG Ai-wu1,2,3、*, ZHANG Xi-zhen1,2,3, and CHEN Yun-sheng1,2,3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less

    Most of the current research focuses on the improvement and application of spatial and spectral resolution of Hyperspectral Image(HSI). It pays little attention to the comprehensive application of radiation resolution. The radiation resolution reflects the range of the dynamic change of the radiation energy received by the sensor. It detects the small change of the radiation energy of the ground object, which also contains rich ground object information. This study proposes a HSI Radiation Bit Depth Residual Quantization Method to construct Low Bit Depth Hyperspectral Image (LHSI) and Residual Hyperspectral Image (RHSI)with different radiation bit depth levels. Through experiments, LHSI and RHSI of different radiation bit depth levels of HSI and their combinations are used to classify ground objects, and their effects on the classification accuracy of ground objects are analyzed. Experiments show that, based on ensuring a certain classification accuracy, 9-bit LHSI retains the main information of HSI; 4-bit RHSI highlights more details of ground objects than the HSI. The combination of 13-bit LHSI and 3-bit RHSI can not only retain the main information of HSI but also highlight the details of the ground object.

    Tools

    Get Citation

    Copy Citation Text

    WANG Juan, ZHANG Ai-wu, ZHANG Xi-zhen, CHEN Yun-sheng. Residual Quantization of Radiation Depth in Hyperspectral Image and Its Influence on Terrain Classification[J]. Spectroscopy and Spectral Analysis, 2024, 44(3): 872

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Oct. 12, 2022

    Accepted: --

    Published Online: Aug. 6, 2024

    The Author Email: Ai-wu ZHANG (zhangaiwu@cnu.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2024)03-0872-11

    Topics