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- 2 Gaussian blurring is used to define an image scale to work in, for interpolation, for computing interest points, and in many more applications. SciPy comes with a module for filtering called scipy.ndimage.filters that can be used to compute these convolutions using a fast 1D separation. All you need to do is: from PIL import Image from numpy import * numpy from scipy.ndimage import filters im = array(Image.open('empire.jpg').convert('L')) = im2 filters.gaussian_filter(im,5) 001-08 T التعليل Here the last parameter of gaussian_filter() is the standard deviation. sagino O 80 (a) q Langla (b) Bia oltes (c) gooliage (d) toteu Figure 1.9: An example of Gaussian blurring using the scipy.ndimage.filters module. (a) original image in grayscale, (b) Gaussian filter with o=2, (c) with σ = 5, (d) with σ = 10. Figure 1.9 shows examples of an image blurred with increasing segma. Larger values gives less details. To blur color images, simply apply Gaussian blurring to each color channel. Exercises…Write a python code that implements dithering as follows:Convert a 24bit image (choose low-resolution image or icon i.e. 400*400) to an 8-bit image.- Show the color lookup table + raster area- the image before and after(use click button)"""You are given an n x n 2D mat representing an image. Rotate the image by 90 degrees (clockwise). Follow up:Could you do this in-place?""" # clockwise rotate# first reverse up to down, then swap the symmetry# 1 2 3 7 8 9 7 4 1# 4 5 6 => 4 5 6 => 8 5 2# 7 8 9 1 2 3 9 6 3 def rotate(mat): if not mat: return mat mat.reverse() for i in range(len(mat)): for j in range(i): mat[i][j], mat[j][i] = mat[j][i], mat[i][j] return mat if __name__ == "__main__": mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] print(mat) rotate(mat) print(mat).
- An 8-bit image has a perfectly normalized histogram. Suppose that each pixel value is ANDed with 1000 0000 , and is set to white if the result of ANDing is non-zero, otherwise is set to black if the result is zero. What is the normalized number of black pixels in the output image? Write the number with 2 decimal points in the box below.Consider the following 8-bit greyscale image: 12 12 12 59 179 254 254 254 12 12 12 59 179 254 254 254 12 12 12 59 179 254 254 254 12 12 12 59 179 254 254 254 Compress the image using Huffman coding. Hint: construct the Huffman table and encode the image scanlines using the table entries.Answer the following Questions and scan them and upload them. File name your register number. 1. Give a single intensity transformation function for spreading the intensities of an image so the lowest intensity is 0 and the highest is L-1. 2. Develop a procedure for computing the median of an n*n neighborhood. 3. Propose a technique for updating the median as the center of the neighborhood is moved from pixel to pixel.
- Task 4: Write a Matlab code to do the following: 1. Read a "cameraman.tif image 2. Make the image smaller to [50, 50] and call it small_img 3. Enlarge the output image from step 2 (small_img) into [400, 400] using nearest neighbor interpolation. 4. Enlarge the output image from step 2 (small_img) into [400, 400] using Bilinear interpolation.7. Build PDA to generate all palindromes containing I's and 0's of odd length (examples 11011,111,101,0011100,etc)Motion History Image (MHI) technique uses a frame differencing inside to generate M(t). In its original form SFD is used. Instead of SFD, we can use a) ABS, b) TFD. Write pseudo-code for each case separately.
- Using any of the following programming languages, design the interface and write the required code to build a simple image compression application. After selecting any raw "grey-scale" image, your program should output a compressed version of the input image. This simple interface should only apply DCT and Quantization to compress the selected image. You should consider the following in your code: - The transformation process should be done using the Discrete Cosine Transform (8x8 block size). - The user must be able to choose either a coarse quantization or fine quantization. - After the quantization process is applied, rescaling and IDCT should be applied inorder to display the compressed image. In addition to your code, you are requested to submit a documentation that illustrates your application and discuss the results. Suggested programing languages: Matlab, Python, Java, Visual C#Computer Science Let C be a black circular disk in front of a white background. The circular disk is parallel to the image plane. This disk is projected on the image plane through a pinhole. What is the shape of the disk’s projection on the image plane? [Hint: A circular disk parallel to the image plane is described algebraically as all 3D points [X,Y,Z]T with (X-X0) 2 +(Y-Y0) 2 =R2 , Z=Z0, where [X0,Y0,Z0] T is the center of the disk and R is its radius.]Assume that I is a grayscale image, I1 is obtained by applying histogram equalization on I, and I2 is obtained by applying histogram equalization on I1. Which of the following statements is DEFINITELY TRUE?