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.

Image Enhancement using Edge Detection Generation of False color composite using single band data Image Classification using Maximum likelihood classification technique
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