Suppose there is a 4* 4 image as shown below, if we reduce the image to 3 * 3 pixels, please give the value of each pixel, and please give the calculation process of bilinear interpolation. 0 1 2 3 0 12 O ABC 1DEF 2 GHI →X 16 2 4 6 2 2 6 8 4 3
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- 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.Connect a 5*7 dot-matrix display to the 8051-microcontroller (Draw the schematic on paper and upload it as a photo). Then, display the content of variable NUMBER on the display, digit by digit every one second. for example if NUMBER=249, then "2" will be displayed for one second, after that digit "4" and finally digit "9" will be displayed for a whole second. Assume that the necessary lookup table exists in Memory at address 0xF000Transcribed Image Text L. Compute the surface area of a cylinder, when its height and diameter is given. A = 2nr2 + 2nrh M. Compute the area of a rectangular prism, when it's all sides is given. A = 2· (h· d + d w+w h) N. Compute the volume of a rectangular prism, when it's all sides are given. Volume = h ·d·w
- Program a simplified Galton board in python. It is required that: The user must select the number of rows n of the board The distribution resulting from dropping the beads should be displayed on the screen. Display an animation where the number of rows n increases over time.All resulting distributions must be scaled to the interval [0, 1], so that it is possible toappreciate the convergence to the normal distribution. Consider n from 1 to 80.Describe an algorithm for converting a greyscale image to a two-bit image (i.e. only using black, dark grey, light grey and white), while preserving as much visual quality as possible. Your algorithm should map every input greyscale pixel to exactly one output pixel.Computer Science Write a program to find the image gradients of any gray scale image of your choice in python only. • Display the original, the gradient in x direction, the gradient in y direction, and the gradient magnitude images. • Apply a simple threshold to the gradient magnitude image and display the gradient magnitude and the thresholding image. You may use 100 as your threshold value or any other appropriate value.
- A robot is initially located at position (0, 0) in a grid [−5, 5] × [−5, 5]. The robot can move randomly in any of the directions: up, down, left, right. The robot can only move one step at a time. For each move, print the direction of the move and the current position of the robot. If the robot makes a circle, which means it moves back to the original place, print “Back to the origin!” to the console and stop the program. If it reaches the boundary of the grid, print “Hit the boundary!” to the console and stop the program. A successful run of your code may look like: Down (0,-1) Down (0,-2) Up (0,-1) Left (-1,-1) Left (-2,-1) Up (-2,0) Left (-3,0) Left (-4,0) Left (-5,0) Hit the boundary! or Left (-1,0) Down (-1,-1) Right (0,-1) Up (0,0) Back to the origin! Instructions: This program is to give you practice using the control flow, the random number generator, and output formatting. You may not use stdafx.h. Include header comments. Include <iomanip> to format your output. Name…"""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).Computer Science For an image represented by a given large 3d numpy array, use numpy to get a neighborhood filter using the mean of the pixels. For example, look through each of the image’s 3×3 window of pixels and replace outlier pixels with the mean value of the others in the 3×3 window. Set the resulting pixel value to be the mean value of a pixel and its eight neighbors. For pixels on an edge, use the mean value of the pixel and its five neighbors. For pixels on corners, use the mean value of the pixel and its three neighbors. If you loop over every pixel then you must store your input and output arrays separately
- Upsampling an Image using Interpolation TechniquesThere are a number of techniques that can be used to upsample an image.In this assignment, you are expected to implement Interpolation methods (such as Lagrangian Interpolation, Divided Difference, etc.) for three different images and compare the results. Example Code Python: orgImage = cv2.imread("dene.png")w, h, d = orgImage.shapexResized = int(w * scale);yResized = int(h * scale);....cv2.imwrite("resizedImage.png", resizedImage) Example Code Matlab:I = imread('pen.png');figure;imshow(I); [w, h, d ]= size(I)R = I(:,:,1);G = I(:,:,2);B = I(:,:,3); %for cubic spline write findcoefficients method[ax,bx,cx,dx ] = findCoefficients(R);[ay,by,cy,dy ] = findCoefficients(G);[az,bz,cz,dz ] = findCoefficients(B); ....R_new = ax(i)*i_d.^3 + bx(i)*i_d.^2 + cx(i)*i_d + dx(i);G_new = ay(i)*i_d.^3 + by(i)*i_d.^2 + cy(i)*i_d + dy(i);B_new = az(i)*i_d.^3 + bz(i)*i_d.^2 + cz(i)*i_d + dz(i);Summary: Given integer values for red, green, and blue, subtract the gray from each value. Computers represent color by combining the sub-colors red, green, and blue (rgb). Each sub-color's value can range from 0 to 255. Thus (255, 0, 0) is bright red, (130, 0, 130) is a medium purple, (0, 0, 0) is black, (255, 255, 255) is white, and (40, 40, 40) is a dark gray. (130, 50, 130) is a faded purple, due to the (50, 50, 50) gray part. (In other words, equal amounts of red, green, blue yield gray). Given values for red, green, and blue, remove the gray part. Ex: If the input is: 130 50 130 the output is: 80 0 80 Find the smallest value, and then subtract it from all three values, thus removing the gray. Note: This page converts rgb values into colors. 461710.3116374.qx3zqy7 LAB ACTIVITY 1 111 4.10.1: LAB: Remove gray from RGB Type your code here. 111 main.py 0/10 Load default template...Summary: Given integer values for red, green, and blue, subtract the gray from each value. Computers represent color by combining the sub-colors red, green, and blue (rgb). Each sub-color's value can range from 0 to 255. Thus (255, 0, 0) is bright red, (130, 0, 130) is a medium purple, (0, 0, 0) is black, (255, 255, 255) is white, and (40, 40, 40) is a dark gray. (130, 50, 130) is a faded purple, due to the (50, 50, 50) gray part. (In other words, equal amounts of red, green, blue yield gray). Given values for red, green, and blue, remove the gray part. Ex: If the input is: 130 50 130 the output is: 80 0 80 Find the smallest value, and then subtract it from all three values, thus removing the gray.