Garillos-Manliguez_Hyperspectral Images of Papaya Dataset 32p

This dataset consists of 4,608 hyperspectral image (HSI) patches of papaya fruit, each with a spatial resolution of 32 × 32 pixels. The patches are extracted from full-frame hyperspectral images acquired using an Imec SNAPSCAN visible/near-infrared (VNIR) hyperspectral imaging system. The system captures 150 spectral channels spanning wavelengths from 470 nm to 900 nm, with an original spatial resolution of 2048 × 1088 pixels. Each patch is stored in the standard ENVI format, comprising a .hdr header file and a corresponding .img binary data file. These patches are intended for use in tasks such as fruit maturity estimation, classification, and spectral analysis.

For detailed information about the data acquisition process and the experimental setup, please refer to the following publication:
Garillos-Manliguez, C. A., & Chiang, J. Y. (2021). Multimodal Deep Learning and Visible-Light and Hyperspectral Imaging for Fruit Maturity Estimation. Sensors, 21(4), 1288. https://doi.org/10.3390/s21041288.
Please cite this article when using the dataset.