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Sensors, Vol. 18, Pages 2045: HyTexiLa: High Resolution Visible and Near Infrared Hyperspectral Texture Images

Sensors, Vol. 18, Pages 2045: HyTexiLa: High Resolution Visible and Near Infrared Hyperspectral Texture Images

Sensors doi: 10.3390/s18072045

Authors: Haris Ahmad Khan Sofiane Mihoubi Benjamin Mathon Jean-Baptiste Thomas Jon Yngve Hardeberg

We present a dataset of close range hyperspectral images of materials that span the visible and near infrared spectrums: HyTexiLa (Hyperspectral Texture images acquired in Laboratory). The data is intended to provide high spectral and spatial resolution reflectance images of 112 materials to study spatial and spectral textures. In this paper we discuss the calibration of the data and the method for addressing the distortions during image acquisition. We provide a spectral analysis based on non-negative matrix factorization to quantify the spectral complexity of the samples and extend local binary pattern operators to the hyperspectral texture analysis. The results demonstrate that although the spectral complexity of each of the textures is generally low, increasing the number of bands permits better texture classification, with the opponent band local binary pattern feature giving the best performance.

Authors:   Khan, Haris Ahmad; Mihoubi, Sofiane ; Mathon, Benjamin ; Thomas, Jean-Baptiste ; Hardeberg, Jon Yngve
Journal:   Sensors
Volume:   18
edition:   7
Year:   2018
Pages:   2045
DOI:   10.3390/s18072045
Publication date:   26-Jun-2018
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