# Segment-Based Clustering of Hyperspectral Images Using Tree-Based Data Partitioning Structures
## 3 Results and Comparisons  
The framework that is shown in Figure 1 has been implemented in MATLAB. The proposed framework performance is evaluated and verified on a number of available standard HSI data sets [35; 36] with ground truth:  
* Salinas scene--collected by the 224-band AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) sensor over Salinas Valley, California, and it is characterized by high spatial resolution (3.7-m pixels) and resolution 512 lines by 217 samples in the wavelength range 0.4-2.5 \(\upmu\)m. Salinas ground truth contains 16 classes.
* Salinas-A is a subscene of Salinas image and it comprises 86 \(\times\) 83 pixels that are located within the same scene as Salinas at [samples, lines] = [591-676, 158-240]. It includes vegetables, bare soils, and vineyard fields, and its ground truth contains six classes.  
* PaviaC is acquired by the ROSIS (Reflective Optics System Imaging Spectrometer) sensor over the city center of Pavia (referred as PaviaC), central Italy. The data set contains 115 spectral bands covering the wavelength ranging from 0.43 to 0.86 \(\upmu\)m, but only 102 effective bands were used for experiments after removing low-SNR and water absorption bands [37]. The original image dimension, 1096 \(\times\) 715 with the spatial resolution of 1.3 m, is used in this experiment. The data set consists of nine land cover classes.
* PaviaU is also acquired by the ROSIS sensor over University of Pavia. The image is of a size of 610 \(\times\) 340 and it has a spatial resolution of 1.3 m. Similar to PaviaC, a total of 115 spectral bands were collected of which 12 spectral bands are removed due to noise and the remaining 103 bands are used for classification [37]. The ground reference image available with the data has nine land cover classes.
* Indian Pines scene was gathered by AVIRIS sensor over the Indian Pines test site in North-western Indiana and consists of \(145\times 145\) pixels and 224 spectral reflectance bands in the wavelength range 0.4-2.5 \(\times\) 10\({}^{-6}\) m. The scene contains two-thirds agriculture, and one-third forest or other natural perennial vegetation. There are two major dual lane highways, a rail line, low density housing, other built structures, and smaller roads. The ground truth available is divided into 16 classes.
* Samson scene is an image with 95 \(\times\) 95 pixels and 156 spectral channels covering the wavelengths from 401 nm to 889 nm. The spectral resolution is 3.13 nm. There are three target end-members in the data set, including \"Rock\", \"Tree\", and \"Water\".
* Jasper Ridge is one of the most widely used hyperspectral image data sets, with each image of size 100 \(\times\) 100 pixels. Each pixel contains at 198 effective channels with the wavelengths ranging from 380 to 2500 nm. The spectral resolution is up to 9.46 nm. There are four end-members latent in this data set, including \"Road\", \"Dirt\", \"Water\", and \"Tree\".
* Urban scene consists of images of 307 \(\times\) 307 pixels with spatial resolution of 10 m and 210 channels with wavelengths ranging from 400 nm to 2500 nm. There are three versions of the ground truth, which contain four, five, and six end-members, respectively. In this experiment, four end-members are used, including \"Asphalt\", \"Grass\", \"Tree\", and \"Rood\".