Image Processing

Digital image processing support is essential in GIS to handle raster data sets such as satellite remotely sensed images, and scanned maps. A custom header is designed in GRAM++ which is appended to every raster image imported into the raster database.

The software provides support for:

• Image Enhancement : The term enhancement is used to mean the alternation of the appearance of an image. Image enhancement includes the following options: Negative, Filters, Edge Detection, Contrast Manipulation, Histogram Equalization.
  

• Image Transformation : Image transformation is performed on an image and the resulting image may have properties which make it more suited to a particular purpose than the original, Image transformations included are arithmetic operations like addition, subtraction, multiplication and division, Principal component analysis and Hue saturation and intensity transform.
  

• Image Classification : This method involves associating each pixel in the image with a label describing a real–world object. Various classification tecniques like Maximum Likelihood, ANN (Artificial Neural Network), Parallelepiped, Minimium Distance to Mean, Fuzzy C-means, K-Means Classification techniques are used.
  

• The module also allows the user to generate False Color Composite (FCC) using various combinations of single band data.
  

• The remote sensing data usually comes as a multiband data. Above mentioned analysis cannot be performed on multi-band data and so such datasets can be separated into individual bands using band separation method.