Python Programming
You have to bring your computer to show software assignments to me in person to the TA.
INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS
Software Assignment -1
- You have to bring your computer to show software assignments to me in person to the TA.
- You must submit a report to the e-learn for each assignment to be graded.
Format of a Typical Report:
- Learners oriented objective of the software assignment (for example, Software Assignment #1)
- Learn how to read/write/manipulate 2D signals (Images).
- Apply basic mathematical operators to implement practical concepts such as “Double Exposure”, “Change Detection”, and “Synthesize novel Images”
- Brief description of data acquisition
- Algorithm and logic used in the assignment
- Display intermediate and final results
- Conclusions: Lessons learned doing the assignment:
- For example, the implementation of the software assignment helped me to learn how practical systems can be implemented using basic operators.
- Write computer programs (using your favorite language, for example, MATLAB or C++) to simulate “Double Exposure”, “Change Detection”, and “Synthesize novel Images using masking concept”.
Hints:
- Double exposure: Add 10-15 images of same object taken under same conditions. I want you to compute the signal to noise ratio and noise variance to explain the crisp image created.
- Change Detection: subtract frames taken from your favorite video or sequence of images.
- Multiplication of image: Use 5+ images of your favorite object, mask different portion of different images and combine them to synthesize a new image. Align images properly before these simple operations to work.
- Align or register (if needed) images using techniques such as “image registration. “
Bonus Points: Bonus point for operations on color images synthesizing aesthetically pleasing image.
- Write computer programs (using your favorite language, for example, MATLAB) to simulate the effect of “image resolution”, “Quantization”, and “Multi-resolution”.
Hints:
- Image resolution: Take your favorite image of size 1024 x 1024, reduce the size by a factor of 2 in both dimension and continue till 32 x32. Display the resized images in 1024 x 1024.
- Quantization: Start with your favorite image. Use the “shift right” operator and force the MSB position to zero. This will reduce the dynamic range to half (for example, 0-255 to 0-127, 0-64,0-32, 0-16, 0-8, 0-4, and 0-2). Explain the effect of quantization and compute the SNR.
- Multi-resolution: reduce the size the image progressively by a factor of 1.72 and display images.
- Bonus Point: If you are enthusiastic try out zoom in and zoom out.
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