INT 404: Image and Video Processing
Lab 1 – INT 404: Image and Video Processing
Start Date: 2024-10-09
Deadline: 2023-10-23
15% of the final marks
Late Submission Policy: 5% of the total marks available for the assessment shall be deductedfrom the assessment mark for each working day after the submission date, up to a maximum offive working days.
Objectives:
1- Introducing the image processing capabilities of Matlab and its Image ProcessingToolbox.
2- Learn to read and display different images.
3- Learn basic image processing steps.
4- Master different image enhancement techniques
Download:
Download the files of lab1-Material.zip from the Learning Mall, unzip the file into a folder lab1- Material, which contains “lenna512_low_dynamic_range.bmp”and “lenna512.bmp”.Tasks:
- Task1: PSNR (5’):Write a function to measure the Peak Signal to Noise Ratio (PSNR) between two grayimages in dB. For the peak value use 255.The PSNR is giv
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃(𝑑𝑑𝑑𝑑) = 10𝑙𝑙𝑙𝑙𝑙𝑙
10(255^2𝑚𝑚𝑚𝑚𝑚𝑚 )Where mse is the mean square error, and it is evaluated as:𝑚𝑚𝑚𝑚𝑚𝑚 = 𝑁𝑁 1 ���𝑖𝑖𝑖𝑖(𝑟𝑟𝑟𝑟, 𝑐𝑐𝑐𝑐) − 𝑖𝑖𝑖𝑖2(𝑟𝑟𝑟𝑟, 𝑐𝑐𝑐𝑐)� 2
∀𝑟𝑟𝑟𝑟 ∀𝑐𝑐𝑐𝑐Task 2 (37’)In this task, we use the monochrome image Lenna (i.e., lenna512.bmp ) to do the followingsub tasks, and let’s call the original image Lenna as I0(both horizontally and vertically) using mean
value. First, describe your algorithm and implement it by yourself. Then, display it andcompare to the original image. Finally, explain your founding in the report; (10’)(b) I1-> up-sampling to I
1’ with the same size of I
0using nearest neighbor interpolation.First, describe your algorithm and implement it by yourself. Then, display it and
compare to the original image. Finally, explain your founding in the report. (12’(c) First, calculate the PSNR between the original image I0and the up-sampledimages,i.e.,nearest, bilinear, and bicubic, respectively. Then, describe the algorithm of bilinear.Finally, Compare the results of different interpolation methods and Explain yourfounding in the report. (15’) (Note: for the bilinear and bicubic interpolation, youcanuse the matlab function directly).
Image
nearest
bilinear
bicubic
PSNR (dB)
- Task 3 (26’)
Import the image “lenna512_low_dynamic_range.bmp” as im_ldr, then finish the following
sub-tasks:
(1) Write a function to generate a piece-wise linear mapping transform to enhance the
contrast of im_ldr; Verify the effectiveness of several mapping transform functions by evaluating the PSNR with respect to the reference image, and show all enhancedmages;Identify the best intensity mapping function you obtained. (10’)
(2) Briefly describe the technique of histogram equalization; Use this technique to enhancethe contrast of the low quality image im_ldr; Display the obtained image and show itshistogram in the report; Compare the current result with the best intensity mappingfunction in (1), and explain your finding. (16’)
- Task 4 (32’)In this task, we use the monochrome image Lenna (i.e., lenna512.bmp ) to do thefollowing sub tasks, and let’s call this reference image Lenna as im.
- a) Add Gaussian white noise with zero mean and variance 16 to the image im and displaythe noisy image. Name it as im_wn. Please write one function to generate this imageinstead of calling matlab function directly. (6’)
- b) Describe the technique of average filter and 代 写INT 404: Image and Video Processing weighted average filter with a 3X3 window,respectively. Then implement both of them by yourself and use the same template inthe slides. Finally, compute the PSNR in the following table and display allfilteredimages and compare them to the original image. You can use add one boundary withthe same as its neighboring pixel values (i.e., nearest neighbor padding). (10’)MethodAverage filter Weighted average filter PSNR (dB)
- c) Describe the technique of Image Averaging, and explain why it can remove noise.Use this technique to remove the noise of im_wn, e.g., average 10 images to getim_wn10, average 100 images to get im_wn100, and average 1000 images to getim_wn1000. You need to implement this by yourself.Display these three images and Evaluate the PSNR of these three images with respectto the reference image im. Comment which one is better by comparing to the mean. (16’) Image im_wn10im_wn100im_wn1000PSNR(dB)Lab Report Write a short report which should contain a concise description of your results and observations.
Include listings of the Matlab scripts that you have written. Describe each of the images thatyou were asked to display.Answer each question completely:
– Do not attach the code at the end of the report, just put the useful code under each question
– The results maybe contain some figures, please add some index and title of each figure
Report format: Single column; Fond size: #12; Page number: no more than 15;
Submission before 2024-10-23.– Electrical version to LM with a rar (ZIP) of all files
- Rar file name: INT404-Lab1-Name-studentID.rar
- One file with same file name of Rar File: Report ( with studentID, name, Lab title on thehomepage)
- One folder: codes and other materials. (I can run it directly)
Marking scheme
80%-100% Essentially complete and correct work.60%-79% Shows understanding, but contains a small number of errors or gaps.40%-59% Clear evidence of a serious attempt at the work, showing someunderstanding, but with important gaps.20%-39% Scrappy work, bare evidence of understanding or significant work omitted.、、<20% No understanding or little real attempt made.This page last modified on 2024-10-08 8:53 AM
