Multi-band images are referred to as multi-spectral or multi-channel or hyper-spectral images. The applications of multi-band image analysis have grown fast in agriculture, ecological environments, commercial geographic information systems, medical science, and so forth. For many tasks related to such applications, objects within images need to be grouped so that, for example, farmland areas can be estimated or areas at different times and economical utilization can be compared. In the past few years, spectral clustering methods have been used to segment images; these outperform the square error clustering methods when dealing with some complicated cluster structures.
As per the above, there is a very wide variety of fields where our tool can be useful, such as:
  • Space-based imaging
  • Weather Forecasting
  • Spectral characterisation of materials and chemical imaging
  • Food analysis and sorting
  • Quality control in industry
  • Hyperspectral analysis of tissue damage
  • Quality control of pharmaceutical products
  • Art analysis and archeology