Indian Pines is a Hyperspectral image segmentation dataset. The input data consists of hyperspectral bands over a single landscape in Indiana, US, (Indian Pines data set) with 145×145 pixels. For each pixel, the data set contains 220 spectral reflectance bands which represent different portions of the electromagnetic spectrum in the wavelength range 0.4−2.5⋅10−6.
78 PAPERS • 2 BENCHMARKS
The Pavia University dataset is a hyperspectral image dataset which gathered by a sensor known as the reflective optics system imaging spectrometer (ROSIS-3) over the city of Pavia, Italy. The image consists of 610×340 pixels with 115 spectral bands. The image is divided into 9 classes with a total of 42,776 labelled samples, including the asphalt, meadows, gravel, trees, metal sheet, bare soil, bitumen, brick, and shadow.
39 PAPERS • 1 BENCHMARK
Kennedy Space Center is a dataset for the classification of wetland vegetation at the Kennedy Space Center, Florida using hyperspectral imagery. Hyperspectral data were acquired over KSC on March 23, 1996 using JPL's Airborne Visible/Infrared Imaging Spectrometer.
16 PAPERS • 1 BENCHMARK
Houston is a hyperspectral image classification dataset. The hyperspectral imagery consists of 144 spectral bands in the 380 nm to 1050 nm region and has been calibrated to at-sensor spectral radiance units, SRU =$ \mu \text{W} /( \text{cm}^2 \text{ sr nm})$. The corresponding co-registered DSM consists of elevation in meters above sea level (per the Geoid 2012A model).
5 PAPERS • 1 BENCHMARK
WHU-Hi dataset (Wuhan UAV-borne hyperspectral image) is collected and shared by the RSIDEA research group of Wuhan University, and it could serve as a benchmark dataset for precise crop classification and hyperspectral image classification studies. The WHU-Hi dataset contains three individual UAV-borne hyperspectral datasets: WHU-Hi-LongKou, WHU-Hi-HanChuan, and WHU-Hi-HongHu. All the datasets were acquired in farming areas with various crop types in Hubei province, China, via a Headwall Nano-Hyperspec sensor mounted on a UAV platform. Compared with spaceborne and airborne hyperspectral platforms, unmanned aerial vehicle (UAV)-borne hyperspectral systems can acquire hyperspectral imagery with a high spatial resolution (which we refer to here as H2 imagery). The research was published in Remote Sensing of Environment.
2 PAPERS • NO BENCHMARKS YET
The LIB-HSI dataset contains hyperspectral reflectance images and their corresponding RGB images of building façades in a light industrial environment. The dataset also contains pixel-level annotated images for each hyperspectral/RGB image. The LIB-HSI dataset was created to develop deep learning methods for segmenting building facade materials.
1 PAPER • NO BENCHMARKS YET