CSE575_KnowledgeCheck_DeepLearningForVideo-BasedRecognition

Help with cg mcq   The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of gray levels allowed for each pixel. The value M and N have to be: a) M and N have to be positive integer b) M and N have to be negative integer c) M have to be negative and N have to be positive integer d) M have to be positive and N have to be negative integer

The pixels in a 3 x 3 image sub-block are as follows: 3 4 2 9 ? 1 3 7 3 (a) Estimate the unknown pixel in the center using both a mean and a median estimator. (b) Repeat if the pixel of value 1 is changed to 25. Are both the mean and median affected? Why or why not?

Q1: Rescale the following image to be 50% smaller than its original size (you should avoid Aliasing) 25 19 17 19 22 23 19 20 22 32 32 33 20 44 43 46 Q2: Rescale the following image to be 200% bigger than its original size using both Nearest neighbor interpolation BİLinear interpolation 25 17 19 19 22 32

Given the 3x3 color image with red, green, and blue pixel values: [90 100 1101 R = 90 100 100 , G = 90 100 110 , B = 80 90 110 190 100 90. [100 110 120] [110 100 110] 80 100 100] 90 100 110] a) Calculate the region covariance matrix of the above image. b) Can you compare the above image with a 2x2 image region: [100 1001 R [90 1001 190 100] [110 105] B = 90 100 G 80 95 using the region covariance approach? Explain your answer.

I need the answer as soon as possible

6. For the following 5 × 5 image, using mirror-padding, calculate the gradient magnitude and angle images using 3 x 3 Sobel operators. 2 3 57 7 7 6 7 6 1 2 14 5 7 6 7 7 3 4 1. 25

Subject= digital image processing (Master of computer application) Please give the proper explanation that covers my whole question.

Calculate what is the maximum viewing distance for a given setup to be able to distinguish all details: - diagonal of the display 2.1 m, - display ratio 4:3, - display resolution: 4K UHDTV. Write down all the calculations. NOTE: Pixel doesn't have to be a square.

For the given 4x4 RGB image below, apply uniform quantization algorithm and find the reduced 64-color palette image. (Hint: divide each color space into 8 regions.) 38,49,35 26,34,19 70,80,72 58,67,50 63,70,54 76,85,82 40,46,44 45,52,45 46,51,47 40,45,38 58,65,49 23,28,8 111,111,99 78,79,63 80,80,56 30,29,1

Data: 000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011111111111111111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111111111110000000000   Use MATLAB code to graph the data set and make it look like the image attached. The x-axis should be time and the y-axis should go to 1.

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1) Obtain the gray level transformation function that stretches gray scale range (0, 10) into (0, 15) shifts range (10,20) to (15,25) and compress range (20,30) into (25,30). 2) Grey level histogram of an image is given below, Compute histogram equalization. Draw the histogram of input & output image. GREY LEVEL 0 1 2 3 4 5 FREQUENCY 790 1023 850 656 329 245 122 81 3) For the 3 bit 4x4 size image perform following operations: (a) Negetion (b) Thresholding with T-4 (c) Intensity leve! slicing with hackground with r1-2 and r2= 5 (d) Plot the image histogram, and find probability density function (PDF)? 2 1 3 4 7 4 2 3 5 5 1 4 6. 4 2 2 1 4

Following figure (next slide) shows the histograms of three different images, and three possible point functions. For each original image, which point operation can best equalize its histogram? Briefly explain your reasoning. h₁(f), a 0 g₁(f) + 255 128 0 64 128 255 f 192 255 f h₂(f) a 0 64 9₂(f)+ 255 128 0 128 192 255 h₂(f) 4 a 0 g3(f) + 255 128 0 128 255 f 128 255

Construct 5 × 5 noisy image matrix from your Student ID as discussed below?Example: Assume your Student ID is 437818854, and then use the first five numbers as rows and thelast five numbers as columns. Use the following formula to fill each pixel value g(x,y) =  Row × Col  + 12

Q1- Assume that an image of 32x32 distributed as follows: Gray level 12 14 15 16 18 19 20 21 22 Num of pixels 74 50 100 250 150 280 30 50 40 a) Draw the image histogram b) Find the equalized histogram

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(a) An image with 8 gray levels is shown in the following figure. Hand calculates histogram equalization to the image. Show how you compute the mappings and the histogram equalized image. [2 0 1 1 01 155 5 1 4 5 4 4 5 4 5 5 5 7 Lo 1 5 6 1- (b) Hand calculates the Sobel edge detection on the image below. Step: (1) apply X operator (convolution) to obtain GX, (2) apply Y operator to obtain GY, (3) combine GX and GY using the "sum of absolute values" to obtain G. Show your GX, GY and G. 0 0 0 0 100 0 100 0 0 0 0 0 0 100 100 100 100 0 0 100 100 100 Image: 0 0 100 100 100 100 100 100 0 0 0 0 100 0 0 100 100 100 100 0 0 0 0 Lo 0 -1 0 11 0 2 -1 0 11 -2 X operator: -2 Y operator: 1 1

13) What does a NOT operation do to the appearance of an image? Perform the NOT operation to this random gray-level image: -150 105 145 75 80 45 50 67 80 130 123 40 37 20 250 23 65 95 220 22 L200 150 255 110 145¹

Perform the histogram equalization on the following image and convert to 24 gray levels Gray level No of Pixels (n) 0 240 1 360 2 480 3 600 4 720 5 840 6 960 7 1080 Provide your answers in the below table format No of PDF (n/N) Gray level (₁) CDF (L-1) *CDF Sk p(rk) 0 1 2 3 4 5 6 7 Gray Level 2 3 No. of pixels (old image) 480 600 No. of pixels (New image) 16 gray level Pixels (n) 240 360 480 600 720 840 960 1080 0 240 1 360 4 720 5 840 6 960 7 1080 8 9 10 11 12 13 14 15

How Laplace operator is used to sharpen an image? Explain your answer with a 4 x 4 pixel image.

RGB to gray:  Take an image from your system and plot both original image and grayscale image of same image in MATLAB. Provide Matlab code and attach both original and grayscale image.

Which spatial filters do you use to reduce the noise if an image is corrupted by(i) salt and pepper noise only,(ii) Gaussian noise only,(iii) both salt and pepper noise and Gaussian noise.Give a single filter name as answer to each cases asked above.

Q: -3 Segment the following image using Fast Scanning Algorithm having threshold value 35. Write down all steps. 100 210 120 190 233 150 110 250 200

Q4: The original histogram of 64 x 64 image in 8 gray levels sketched below. 1. Find the histogram equalization mapping, 2. Show the resulting image with its histogram. 15. 0.2 T 6.15 0- 0.05 Original Histogram

Q1- B) Answer the questions: A. What does the "salt and pepper" noise look like? And how can it be removed? marks) B. What is the difference between the spatial resolution and intensity level resolution of an image?

2. [Vector Quantization] Please consider the 4 pixel by 4 pixel image below: 202,118,148 237,141,151 250,172,164 239, 166, 169 122,36,41 175,53,18 228,43,118 233, 134,60 70,49,62 86,49,35 150,39,43 169,56,58 151, 132, 233 169, 135,244 179,135,244 174,139,244 The table contains the RGB values of the sixteen pixels. All RGB values are in 8-bit, i.e. from 0 to 255. We intend to quantize the image into 4 levels of color via K-means clustering. a) Assuming we have initial quantization levels of (70,70,70), (120,120,120), (155,155,155), (255,255,255) and use Euclidean distance as a measurement of error calculate the result of the first step of the K-means clustering operation. This includes which quantization level each of the pixels will be quantized to, and what the modified quantization vector would be after the first adjustment. b) Compute a reasonable final set of quantization levels for the image. You can use any programming language you are familiar with.