Questions:

1. Load the image peppers.bmp into a variable A. Display the loaded image A on figure 1 with the figure title as Original RGB color Image.

2. Convert image A into a grayscale image and store it as B.

Transpose image B as TB.

Vertically flip image B as VB.

Horizontal flip image B as HB.

See flipud and fliplr functions in Matlab.

Display images B, TB, VB, and HB on figure 2 with the corresponding location of upper left, upper right, bottom left, bottom right with corresponding title B, TB, VB, and HB.

Display the maximum, minimum, mean, and median intensity value of B on the Matlab console.

3. Normalize image B to C, whose data type is double and whose values fall in the range of [0, 1]. Display image C on figure 3 with the title Normalized Grayscale Image as the figure title.

Save image C in the png format to a file called *_C.png where * should be your first name.

4. Perform binary thresholding on the original normalized grayscale image C. A threshold 0.4 is chosen and all values in C greater than the threshold are set to 1, otherwise set to 0, leading to a new image bw1. Please finish this task without calling the Matlab built-in function im2bw. Then, please finish the same task by calling the Matlab built-in function im2bw, leading to a new image bw2.

Display bw1 and bw2 side-by-side on figure 4 and label the two images with My method bw1 , and Matlab method bw2, respectively.

If bw1 and bw2 are the same, display bw1 and bw2 are the same as the console output, otherwise display bw1 and bw2 are not the same as the console output.

5. Write a Matlab function MyBlur to replace all 16 pixels in each non-overlapping 44 block of any input image with their average intensity value. The prototype of MyBlur function is defined as follows:

function [BI] = MyBlur(I); where I is the original image and BI is the blurred image, where I can be either one 3-channel RGB color image or one single-channel grayscale image. See mean function in Matlab.

Call this function in your main script to blur the color image A and get the blurred image to variable A2.

Call this function in your main script to blur the grayscale image B and get the blurred image to variable B2.

Display images A, B, A2 and B2 from left to right and top to bottom with the appropriate titles on figure 5.