Hyperpectral Imaging Case Study

spectroscopy which is defined as a combination of imaging and spectroscopy[2]. The modality of the imaging system will be a hyper cube with 2D spatial information and spectral information[14]. The materials in the scene are identified using spectral information. The location in the scene is identified using spatial information. In addition to image information, the classification and identification information is provided in Hyperspectral imaging systems[4]. It is useful for various industrial and other applications, which are in research level[20]. The need for Hyperspectral Imaging is on increasing level owing to accessibility and availability of the immediate treatment for the snail fever[43]. It is cost effective with high performance
The entire spectrum in the image is acquired at each point in hyperspectral data for researching about the medicine for the snail fever[29]. The spatial relationship with in the spectra neighbourhood is the major advantage of hyperspectral imaging[5]. The major disadvantage in hyperspectral imaging is fast computers with sensitive detectors and the large amount of data with storage capacities are needed for the analyzing of the hyperspectral data. It will be helpful in fabricating systems in spite of its cost and high performance. Snail fever is spread by contact with the fresh water contaminated with the parasites in the water body. The disease is most common in the developing countries than the developed countries[42]. The parasite is diagnosed by the presence of the parasite in the urine or the stool of the infected person[6]. The World Health Organization recommends the medicine praziquantel for the treatment of snail fever[28]. But there are more side effects for this medicine. There is a chance for re-infection by using the praziquantel, so there is an immediate and urgent need for discovery of new medicine for the snail
The title for the image is given as the Binary Hysteresis Image[34]. The Binary Hysteresis of the image is processed using the canny filter for removing the noise in the image. The morphological operation opening and thinning is done for analysis of Binary Hysteresis image processing. Figure: 4.7 Watershed Lines
The Binary Hysteresis image is used analysis of the watershed lines in the image[24]. The title for the image is given as the Watershed Lines. The Watershed Lines of the image is processed using the magnitude of the image and it is converted to rgb of the image. The magnitude of the image is used for the analysis of the watershed lines of the image. Figure: 4.8 Statistical Region Merging Image
The Statistical Region Merging Image is analyzed using the Binary Hysteresis of the image[41]. The title for the image is given as the Statistical Region Merging Image. The Statistical Region Merging of the Image is processed using the order of membership and maximum iteration in the image. The Convergence difference and the number of cluster are to be analysed for the statistical region merging image. Figure: 4.9 Segmented