ELE 473-573 Sayısal Görüntü İşleme

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ELE 473-573 Digital Image Processing/HWs

HW 1, due May 27, Monday, 24:00, send by email

Implement (i) filtering/denoising with a mask, (ii) a thresholding algorithm using the following logic:

A good threshold value is at a value where the number connected regions in an image do not change as much.

Thus your thresholding algorithm steps are:

1. For each candidate threshold value (from 0 to 255), calculate the number of connected regions in your binary image (use MATLAB's builtin code for number of connect regions)

2. Based on these values of number of connected regions, pick an optimum T value.

For testing:

1. Take the photograph of a text image (black text on white background).

2. Add artificial noise to this image with varying noise level 1. salt and pepper noise, 2. Gaussian noise

3. Denoise this image using smoothing filters, sharpening filters, median filters (write your own code for filtering)

4. Test a bunch of these combinations and see observe the effect on the quality of thresholding.

Email to me a ***single pdf*** that has, (i) your codes for filtering and thresolding written as MATLAB functions, (ii) your script for testing, (iii) results including varying noise levels, results with various denoising. You shold show/plot original, noisy, denoised, and thresholded images foe each cases.

HW 2, due June 10, Monday, bring to the class

HW 3, due June 10, Monday, bring to the class

HW 4, due July 15, Monday, bring to the class

HWs 5 and 6, due July 29, Monday, drop in my mailbox