Image-proceessing-basics-matlab-python-2

Image processing basics Matlab and Python

1. Write a MATLAB/Python function which performs four arithmetic operations between two images.
2. Take a noisy image. Write a MATLAB/Python function which reduces the noise by averaging the input image by 2, 8, 16, 32 and 128. Compare all the resultant images and find which one is noise free.
3. Write a program which implements all the types of linear spatial filters using MATLAB/Python functions.
4. Implement a program for image convolution and correlation using a rectangular convolution mask of any odd size. The mask should be input as an ASCII text file. Test your program using the following convolution kernels: a. 3×3 averaging b. 7×7 averaging c. 11×11 averaging
5. Write a MATLAB/Python function for implementing median filtering of an image. Add salt and pepper noise to it. Apply the median filter to the noisy image and compare the results.
6. Detect the edges in an image using the following methods and compare the relative performance of these methods: a. Sobel b. Prewitt c. Roberts d. Laplacian of a Gaussian (LoG) e. Canny
7. Write a MATLAB/Python function for smoothing an RGB color image with a linear spatial filter.
8. Write a MATLAB/Python function for sharpening an RGB color image with the Laplacian filter mask.
9. Take a sample image of size 256×256. Write a MATLAB/Python function for implementing DFT filtering with (a) with padding and (b) without padding. Compare the results.
10. Write a MATLAB/Python function to implement various low-pass or smoothening frequency domain filters.
11. Write a MATLAB/Python function to implement various high-pass or sharpening frequency domain filters.
12. Write a MATLAB/Python function to detect straight lines using horizontal, vertical and diagonal filter masks.