Wavelet-based compression method for scale-preserving in VNIR and SWIR hyperspectral data.

ABSTRACT:

Purpose

Hyperspectral imaging (HSI) collects detailed spectral information across hundreds of narrow bands, providing valuable datasets for applications such as medical diagnostics. However, the large size of HSI datasets, often exceeding several gigabytes, creates significant challenges in data transmission, storage, and processing. We aim to develop a wavelet-based compression method that addresses these challenges while preserving the integrity and quality of spectral information.

Approach

The proposed method applies wavelet transforms to the spectral dimension of hyperspectral data in three steps: (1) wavelet transformation for dimensionality reduction, (2) spectral cropping to eliminate low-intensity bands, and (3) scale matching to maintain accurate wavelength mapping.

SUBMITTER: Biswas H 

PROVIDER: S-EPMC12285520 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature