Project 5 - Color Image Processing (Due 11/7)

Task 0: Short answer problems (15 pts)

Task 1: Pseudo-color processing (30 pts.)

Find any gray-scale image provided in the testimage website.

  • Transform this image to a color image using intensity slicing (choose as many color levels as you think is appropriate).
  • Transform the same image to a color image using gray level to color transformation method in the spatial domain.
  • Transform the same image to a color image using gray level to color transformation method in the frequency domain.

    Task 2: Color image processing (40 pts.)

  • (10/5 pts.) Use histogram equalization to enhance the flower image. (In your report, describe the procedure you use or plot the block diagram)
  • (20/15 pts.) Use median filter to reduce the impulse noise in this color image (oldmovie.ppm). Compare the results of applying the filter on the I component ONLY using the HSI model and that on RGB components using the RGB model. Provide the difference image for comparison. (In your report, describe the procedure you use or plot the block diagram)
  • (10/10 pts.) Use Wiener filter to deblur this color image (lenablur.ppm). (I used a 3x3 Gaussian kernel to blur the original lena using gimp. The 3x3 Gaussian kernel can be approximated in spatial domain by 1/16 [1 2 1; 2 4 2; 1 2 1]. Since I don't know exactly what kind of Gaussian kernel used in gimp, this is only an estimation. Therefore, if your inverse filter doesn't give you expected solution, you should know why and comment on it in your report)
  • (0/10 pts.) Read Sec. 6.7.3 and derive the edge image from "peppers.ppm"

    Task 3: Color correction (15 pts.)

    This task is to help students get hands-on experience in color correction of pictures taken under inappropriate exposures. You are given three images (one of them is captured under normal exposure). Try to use this as a reference and correct the other two.