6533b824fe1ef96bd12814de
RESEARCH PRODUCT
GHOST: GRADIENT HISTOGRAM OF SPECTRAL TEXTURE
Hermine ChatouxRui Jian ChuNoël RichardChristine Fernandez-maloigneJon Yngve Hardebergsubject
business.industryHyperspectral imagingPattern recognitionGrayscaleTexture (geology)MetrologyImage (mathematics)gradientmetrology[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Feature (computer vision)HistogramComputer Science::Computer Vision and Pattern Recognition[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]spectralGraphical modelArtificial intelligencebusinesstextureMathematicsdescription
International audience; A gradient-based texture feature for hyperspectral image is formulated with straightforward application to grayscale and color images. Processed in full band, GHOST is expressed as a four-dimensional probability density distribution encompassing joint metrological assessment of spectral and spatial properties. Its performance is close to Opponent Band Local Binary Pattern (OBLBP) in HyTexiLa texture classification (91 %-99 % accuracy) with feature size 0.2 % of OBLBP's.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-03-24 |