Suppose the size of the image is N x N, estimate the number of operations (an operation is an addition or multiplication of two numbers) saved if we apply the 1D filters g andh sequentially instead of applying the 2D filter K. Express your answer in terms of N and k. Ignore the image boundary cases so you don't need to do special calculations for the pixels near the image boundary.
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Solved in 2 steps with 1 images
- Suppose we have an input image f(x,y) shown below. 0 1 2 3 4 2 2 2 2 2 2 4 5 6 7 0 1 2 3 4 0 0 1 5 7 Plese compute the gradient at point (2,3) (Write ansewer in the first blank) (2,4) (Write answer in the second blank) (3,3) (Write ansewer in the third blank) (3,4) (Write answer in the fourth blank) using Sobel Operator. gradient (x,y) =|Gx|+|Gyl.Restate the basic global thresholding algorithm in Section 10.3 so that it uses the histogram of an image instead of the image itself.What would be the result of adding a positive constant (scalar) to a monochrome image? What would be the result of multiplying a monochrome image by a positive constant less than 1.0?
- """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 image is going to be warped by the transformation f using backward mapping. (i) What is the process of backward mapping as opposed to forward mapping? Which one is generally perferred and why? Are there any circumstances in which the preferred option is impossible? (ii) The warping is performed, however, the result looks 'blocky' - smooth lines have become jagged. Why has this occured? Name a solution that the programmer could implement to improve the quality.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?
- subject : smart computing To animate an object while making the movements look realistic, we need to take care of acceleration and deceleration. With nonlinear interpolation, we can do that by using varying time steps using constant time steps fixing the number of inter between frames reducing the number of inter between framesHello, how can I make my images look like slanted order in the attached image from my code? My code just has them stacked on top of each other.For an object detection problem, assume you are designing a YOLO like model to do the job. Your input image size is 127x127 (RGB). We are looking for a 3x3 output grid size. The number of classes is 20 and for each cell in the grid, we are considering 2 anchors. Design the CNN network and as a designer feel free to set your network's hyper-parameters as you wish. The output of your network needs to show the final height, width, and the channel. You do not need to include post-processing (nan-max suppression) step for YOLO. In Python-
- Consider the given image. Apply a non-linear filter that can effectively remove the salt and pepper noise and provide the filtered image. Assume border pixels are replicated for filter evaluation at the edges and kernel size is 3 x 3.Q1 Suppose an image has a line having three points with (x,y) coordinates (1,2), (2,3), and (3,4) (assume the image coordinates starts from (0,0)). What will these points be in the Hough space (m, b)? Draw them in Hough space with exact coordinates mentioned, where (m, b) are the parameters representing the slope and intercept of the line. What information do you get from the resultant Hough space?Use python code with "def mirror(img):" but without cv2, numpy or PIL mirror(img) - Flips the image img left-to-right, and returns a new image with the result. Use the cmpt120image.getBlackImage() function which returns a new canvas to draw on.