Modern Trends in Hyperspectral Image Analysis: A Review <s> D. UNDERSTANDING SPECTRAL SIGNATURES <s> Introduction One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spedral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 pm) of the spectrum. ‘l’his region is covered by modern imaging spectrometers such as AVIRIS. The challenge is to identi~ the materials from absorption bands in their _ and determine what specific analyses must be done to derive particular parameters of interest, mnging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. <s> BIB001 </s> Modern Trends in Hyperspectral Image Analysis: A Review <s> D. UNDERSTANDING SPECTRAL SIGNATURES <s> Image spectroscopy (IS) is an important tool for the noninvasive analysis of works of art. It generates a wide sequence of multispectral images from which a reflectance spectrum for each imaged point can be recovered. In addition, digital processing techniques can be employed to divide the images into areas of similar spectral behavior. An IS system designed and developed in our laboratory is described. The methodology used to process the acquired data integrates spectral analysis with statistical image processing: in particular, the potential of principal-component analysis applied in this area is investigated. A selection of the results obtained from a sixteenth-century oil-painted panel by Luca Signorelli is also reported. <s> BIB002
Materials present on the surface of Earth absorb, transmit and reflect electromagnetic radiations from the sun in a unique way. Hyperspectral sensors allows us to measure all types of electromagnetic energy within a specified range as it interacts with materials, thus allowing us to observe the distinct features and changes on earth's surface. Reflectance is the measure of electromagnetic energy bouncing back from a material's surface. It is a ratio of reflected energy to incident energy as a function of wavelength  . Reflectance is 100% if all the light energy of specific wavelength striking the object is reflected back to the imaging sensor; on the other hand reflectance is 0% if the entire incident light of specific wavelength is absorbed by the object. In most practical cases reflectance values lie in the range [0, BIB002 . In a specified range of electromagnetic spectrum, the reflectance values of different materials present on the earth's surface such as soil, forest, water and minerals can be plotted and compared. Such plots are labeled as spectral signatures or spectral response curves''  . Figure 2 demonstrates a general model of spectral signatures of different materials present on the earth's surface. Remotely sensed images can be classified using these spectral signature plots, as each material present in an observed scene has its own unique spectral signature. The more the spectral resolution of an imaging sensor, the more classification information can be extracted from spectral signatures. Hyperspectral sensors have high spectral resolution than multispectral sensors and thus provide the ability to distinguish more subtle differences in a scene. Hyperspectral imagery has been utilized by geologists for mapping the land and water resources BIB001 . It is also utilized to map heavy metals and other hazardous wastes in historic and active mining areas. The spectral responses of green vegetation, dry bare soil, and clean water are compared graphically in Figure 3 . It is observed that the reflectance curve for bare soil has fewer variations as compared to that of green vegetation. This is because of the fact that the factors that affect soil reflectance vary in a narrow range of electromagnetic spectrum. These factors include soil texture, presence of minerals such as iron, surface roughness and moisture content in soil  . Spectral signatures of green vegetation have basins in the visible range of the spectrum that indicates the pigmentation in the tissues of the plant. Chlorophyll is the primary photosynthetic pigment in green vegetation  , it absorbs strongly in red (670 nm) and blue (450 nm) regions called the chlorophyll absorption spectral bands. When a plant is under stress so that the chlorophyll growth is reduced, in such cases the amount of reflectance in red (670 nm) regions increases  . The spectral response of water has distinctive characteristics of absorption of light in near infrared and beyond. Common factors affecting spectral response of water are the suspended sediments and increases in chlorophyll levels. In each case spectral response will be shifted accordingly showing the presence of suspended sediments or algae in water  .