Details
DIPS is primarily aimed at introductory digital image processing courses in remote sensing.DIPS covers a core body of digital image processing concepts. DIPS has been specifically designed to expose detailed calculations of image processing algorithms using small sample images. The users ( students and teachers) can change these small sample images to build their own examples and add to the pool of exercises.
Concepts covered by DIPS include :
- Additive
and Subtractive Primary Colours
- Display of
Colour on Multiband Digital Images
- Gun Band
Assignments
- Linear
Contrast Stretching
- BSQ,BIL
and BIP Digital Data formats
- Line
dropout and Salt and Pepper noise removal
- Operation
of Low Pass and high pass convolution filters
- Image
Ratioing
- Normalized
Vegetation Difference Index
- Image
Differencing (subtraction)
- Linear
Edge Enhancement
- Density
Slicing
- Supervised
Classification
- Signature Definition
- Minimum
Distance to Mean Classifier
- Parallelepiped Classifier
- Comparison of Classification Outputs
- Accuracy
Assessment
- Random
Selection of Pixels on Classified and Ground maps
- Computation of Error Matrix and % Correct
- Omission
and Commission Errors
- Computation of Kappa Statistic
DIPS permits changes of Image Values, filter kernel values etc such that users can build their own examples. There is a text based help for each module and a set of exercises which act like a guided tour to the sofware and tries to lead towards an in-depth view of the concept.The complete MS Word help file containing all help screens and exercises can be downloaded from the main page of this site. Most screens are however quite intutive and should not require reference to help screens. If more exercises become available by way of contributions from users, I plan to post them on this site.
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