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Q1:Can use MATLAB or Python 1) Implement bit plane coding and design a GUI for real time progressive transmission demonstration. 2) Implement Burt-Adelson's pyramid method using Gaussian windows and design a GUI for real time progressive transmission demonstration. Also give explanation how each of the question is done. Please note that your GUI demonstration must be included as a package so that they can be run on a computer for grade evaluation.See Answer
Q2:Given a row of pixel: [12 12 18 15 16 17 18 18], use the following two prediction models and set of quantization parameters to calculate distortion metrics SAD (sum of absolute difference) between original and reconstructed pixel values. a. Prediction model 1: copy the previous pixel. QP: (2, 4, 6, 8, 10, 12} b. Prediction model 2: average of two previous pixels. QP: (2, 4, 6, 8, 10, 12)See Answer
Q3:Prediction model 2: average of two previous pixels. QP: {2, 4, 2. Draw the flowcharts of the process. 3. Plot line graph for the predictive models (x-axis: QP, y-axis: SAD).See Answer
Q4:4. Write a conclusion based on your observations and quantitative results.See Answer
Q5:Cover Page: Your PDF document should begin with a cover page that includes your name, the title of the class or project, and the date of submission. This provides basic information about the document. Image Assigned with Source Reference: Include the image that has been assigned to you for the project. Alongside the image, provide a source reference indicating where the image came from. Single Color Band Images (Figure 2): Include a section in your PDF document where you display single color band images. This likely involves splitting the original image into its RGB color channels (Red, Green, Blue) and displaying them separately. Value and Luminance Images (Figure 3): Similar to Figure 2, you should display value and luminance images. This might involve converting the image to a different color space (e.g., HSV or YUV) and displaying the appropriate channels. RGB Histograms and Luminance Histogram (Figure 4 and Figure 5): Show histograms for the RGB color channels (Red, Green, Blue) and the luminance channel. Histograms are graphical representations of the distribution of pixel intensities in an image. Appendix with Script Files: Include an appendix section in your PDF document. In this section, provide script files that you used to generate the results shown in the figures. These script files should be clearly labeled and commented so that anyone reading your document can understand how you processed the images and created the figures./nOverall, this task involves presenting and explaining various visualizations and images related to digital image processing. It also requires you to share the scripts or code you used to generate these visualizations. The purpose is likely to demonstrate your understanding of image processing techniques and your ability to implement them programmatically. Make sure to follow any specific guidelines or requirements provided by your instructor or the assignment prompt, as they may have additional instructions or expectations. provided-additional lecture slides You have to make report, give MATLAB code and give graphs as well.See Answer
Q6:(Q1) y4m files: What is a y4m file and how do they differ from yuv files?See Answer
Q7:(Q4) Quality Analysis: Download VLC player, play the original y4m followed by the five compressed variants for each video. Describe your observations about the content and quality when playing in a full scre mode. Repeat playback in a window about 1/4 of your screen and describe your observations. screenSee Answer
Q8:(Q5) RD Analysis: Compare the encoding performance on the five different videos using two different codecs i.e., mpeg-2 and h264. Plot bitrate on the x-axis and PSNR on the y-axis. Show two curves for two codecs and one plot per video. Explain the results. P:S: Please provide relevant screenshots.See Answer
Q9:(Q3) Encode each of these videos at the following target bitrates using MPEG-2 and H264: Bitrate BR1 BR2 BR3 BR4 BR5 BRO (Bitrate Offset) = ceil (Last 3 digit (Z#)/2) For instance, if Z123456789, BRO=ceil (789/2); if Z234564013, BRO = ceil (013/2). BR1 BR2 Input bitrate 5000 BRO 4000 - BRO For each video, complete the following table with actual bitrate achieved, corresponding Y PSNR and encoding time collected from the output of the fimpeg encoding process. Record data in one table for each of the five videos. Video Name: Sunflower BR3 BR4 BR5 3000 BRO 2000 - BRO 1000 BRO Bitrate achieve d (MPEG 2) PSNR (MPEG 2) Encoding Time (MPEG 2) Bitrate PSNR achieved (H264) (H264) --Encoding Time (H264)-See Answer
Q10:(Q1) y4m files: What is a y4m file and how do they differ from yuv files?See Answer
Q11:(Q3) Encode each of these videos at the following target bitrates using MPEG-2 and H264: Bitrate Input bitrate BR1 5000 - BRO BR2 4000 - BRO BR3 3000 - BRO BR4 2000 - BRO BR5 1000 - BRO BRO (Bitrate Offset) = ceil (Last 3 digit (Z#)/2) For instance, if Z123456789, BRO-ceil (789/2); if Z234564013, BRO = ceil (013/2). For each video, complete the following table with actual bitrate achieved, corresponding Y PSNR and encoding time collected from the output of the ffmpeg encoding process. Record data in one table for each of the five videos. Video Name: Sunflower BR1 BR2 BR3 BR4 BR5 Bitrate achieved (MPEG 2) PSNR (MPEG 2) Encoding Time (MPEG 2) Bitrate achieved (H264) PSNR (H264) Encoding Time (H264)See Answer
Q12:(Q4) Quality Analysis: Download VLC player, play the original y4m followed by the five compressed variants for each video. Describe your observations about the content and quality when playing in a full screen mode. Repeat playback in a window about 1/4 of your screen and describe your observations.See Answer
Q13:(Q5) RD Analysis: Compare the encoding performance on the five different videos using two different codecs i.e., mpeg-2 and h264. Plot bitrate on the x-axis and PSNR on the y-axis. Show two curves for two codecs and one plot per video. Explain the results.See Answer
Q14:(Q1) y4m files: What is a y4m file and how do they differ from yuv files?See Answer
Q15:(Q2) Use ffprobe to find the resolution of these videos: Video Width Height sunflower touchdown_pass red_kayak crowd_run witcher YUV format Frame RateSee Answer
Q16:(Q3) Encode each of these videos at the following target bitrates using MPEG-2 and H264: Input bitrate 5000 - BRO 4000 - BRO 3000 - BRO 2000 - BRO 1000 - BRO Bitrate BR1 BR2 BR3 BR4 BR5 BRO (Bitrate Offset) = ceil (Last 3 digit (Z#)/2)See Answer
Q17:(Q4) Quality Analysis: Download VLC player, play the original y4m followed by the five compressed variants for each video. Describe your observations about the content and quality when playing in a full screen mode. Repeat playback in a window about 1/4 of your screen and describe your observations. (Q5) RD Analysis:See Answer
Q18:(Q5) RD Analysis: Compare the encoding performance on the five different videos using two different codecs i.e., mpeg-2 and h264. Plot bitrate on the x-axis and PSNR on the y-axis. Show two curves for two codecs and one plot per video. Explain the results. P:S: Please provide relevant screenshots.See Answer
Q19:Lab 5: Spatial Filter Objectives: 1. Practice lowpass smoothing filter on a given image. 2. Practice highpass filter on a given image. 3.Undestand the principle of geometric transformation; 4. Practice geometric transformation using Matlab command. A complete lab report including the following: Summarized learning outcomes. • Finish Exercises as results. MATLAB scripts should be reported properly as appendix. ● Exercise 1: (1) Research Matlab commands, fspecial, imfilter, filter2. (2) Read the image testpattern 1024.tif. Use box filter of size 3 by 3, 11 by 11, and 21 by 21 on this image. Observe the effects. Try different values, choose a box filter which is large enough to blur the image so that the large letter "a" is barely readable, and the other letters are not. (3) Read the image testpattern 1024.tif. Use Gaussian filter of size 21 by 21 with o = 3.5, and size of 43 by 43 with o = 7 on this image. Observe the effects, compare with the results of box filter. Try different values, choose a gaussian filter which is large enough to blur the image so that the large letter "a" is barely readable, and the other letters are not. Exercise 2: (1). Read the image blurry-moon.tif and sharpen it using the Laplacian kernel. (2). Read the image blurry-moon.tif and sharpen it using unsharp masking. Use a Gaussian lowpass kernel of your choice for the blurring step. Display your final result. (3) Improve the sharpness of your result using highboost filtering. Display the final result. Compare the results with (1) and (2). Exercise 3: (1) Research Matlab commands, affine2d, imwarp, imrotate, imtranslate, imresize. (2) Read the image, cameraman.tif. Scale the image in the following different ways. (a) 2 times of x, 2 times of y. Here x is the horizontal direction (columns), y is the vertical direction (rows); (b) 2 times of x, 0.5 times of y; (c) 0.5 times of x, 1 time of y. (3) Read the image, cameraman.tif. Rotate the image in 60°, -60°. Compare different interpolation methods. (4) Read the image, cameraman.tif. Translate the image to [10 20], [-20 50], [20, -30]. (5) Read the image, cameraman.tif. Choose your own values to create vertical and horizontal shear effect. Exercise 4: Based on the principle of affine transformation, write your own function to perform image translation, translation(image, tx, ty), where image is a grayscale image and tx and ty are translation factors (they can be any real number: positive, negative, or zero) in the x (horizontal) and y (vertical) directions. The output image should be of the same size as the input, and its background is black. Test your function by translating image cameraman.tif by half its height in the positive vertical direction and by one-fourth of its width in the positive horizontal direction.See Answer
Q20:Exercise 2: (1). Read the image blurry-moon.tif and sharpen it using the Laplacian kernel. (2). Read the image blurry-moon.tif and sharpen it using unsharp masking. Use a Gaussian lowpass kernel of your choice for the blurring step. Display your final result. (3) Improve the sharpness of your result using highboost filtering. Display the final result. Compare the results with (1) and (2).See Answer

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