## HW2## Due on Mar 4 (30 points)(10 points) Please use two photos of your own (please don't use stock photos) to create a composting image with one side from one image and another side from another image. Please decompose your images into a Laplacian pyramids with **5**levels (Note that the width and height of your images need to be a product of \(2^5=32\). You should resize them otherwise).Extra credit (5 points). Create a trackbar to vary the number of levels of decomposition as shown in class using the cvui package.
(10 points) Please use the same photos as in Q2 to create a hybrid image (see this). Basically you just need to add a low-pass filtered image of one photo with a high-pass filtered image of another one. The simplest approach is probably approximating a low-pass filter with a Gaussian filter and a complementary high-pass filter with (\(1-\)“Gaussian filter”). That is, we can obtain a high-pass filtered image by subtracting the original image by a low-pass filtered image. Of course, you may also achieve something similar by playing with the fourier transformed images or discrete cosine transformed (DCT) images also. Extra credit (5 points). Add a trackbar to vary a parameter of the low-pass filter Extra credit (5 points). Add a trackbar to vary a parameter of the high-pass filter Extra credit (5 points). Add a trackbar to vary the relative weight of the two images N.B. Feel free to add more trackbars to help adjust the perceptual quality of your outcome.
(10 points) Let \((x,y,1)^\top\) be the homogenous coordinates of an input image. Write down matrices \(M\) such that the output image \(M (x,y,1)^\top\) is A shift of the input image to the left by 10 units. A shift of the input image up by 10 units. A rotated image of the input image by \(30^o\) A scaled image of the input image by 2 times (in both width and height) A mirror image of the original
For all the above questions, please submit a pdf containing the source code the data (photos) you used (if applicable) a screenshot of the output result
Please upload your solution to Canvas before the due date. |