Tools: Scilab with SIP toolbox, grayscale test and sample images
Procedure: We begin with a grayscale image of three gray levels from white to black. Simultaneously we use a real world image (in this case a grayscale image of the Apollo 13 Mission Patch) with more than three gray levels.
We model the different types of noise using mathematical models presented and add these noise matrices to both the test image and the real-world image. The following plate shows the images with different noise models added:
From top to bottom, the noise models are: Exponential, Gamma, Gaussian, Salt and Pepper, Uniform and Rayleigh noise. The added noise is then filtered on all the images using a variety of filters, described in the text (Arithmetic mean, Geometric mean, Harmonic mean and contraharmonic mean filters). The images above are processed using each of these filters and the results are shown below for each of the added noise types:
1. Exponential Noise
2. Gamma Noise
3. Gaussian Noise
4. Salt and Pepper Noise
5. Uniform Noise
6. Rayleigh Noise
Evaluation: For correct noise models and filtering a grade of 10 is acceptable.
Acknowledgements: I would like to thank Mr. Panganiban for the invaluable assistance in this activity.
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