CS 117 Assignment: Median Filters

Photographs are often a mess. Sometimes there's a a hair or a scratch on the negative when you print a photograph. Still photographs taken from television broadcasts or from worn video tapes are often filled with static. Even photos taken with digital cameras might show signs of scratches or smudges on the lens. There are many ways an image can accumulate pixels that show "noise" instead of the intended subject.

One way to eliminate some kinds of noise is a median filter. The idea behind a median filter is that most pixels are surrounded by pixels of the same or similar color. If one pixel has an unexpected color (white for a scratch on the lens or black for a hair on the negative, for example), the surrounding pixels are probably still okay. If we somehow let a pixel's neighbors vote on the pixel's proper color, we might be able to get rid of noisy pixels.

Here's one way to arrange such a vote. Start with a grayscale image. Cycle through all the pixels in the image with the usual double loop over the rows and columns of the image. For each pixel P:

• Collect the gray values for some of the P's neighbors. The neighborhood could be a square of a particular radius, for example, where the radius-1 neighborhood would consist of P itself plus the eight surrounding pixels.
• Sort the gray values you have collected, smallest gray level to largest.
• Pick the middle gray value of your sorted list. The gray level of this pixel is the median gray in the neighborhood. Use that median value as the new color for P.

The left image below is a gray version of an image, with some artificial scratching added to it. Using the median filter described above, with radius-1 square neighborhoods, we get the image on the right. At the cost of a bit of blurring and flattening of the grays, we have nearly eliminated the severe damage of the diagonal scratches.

It's interesting to see that some images clean up better than others. In this scene, for example, the same median filter doesn't do nearly as good a job of fixing the problem (any ideas why?).

Your mission

We will be adding more methods to PhotoLab. You can use the PhotoLab that you used for the previous assignment, or you can start again from scratch if you wish. Here are the methods that your PhotoLab class should have:

• public PhotoLab(EzImage image)
  This is the constructor. The input parameter is the source image.
• public EzImage getOldImage()
  This returns the current EzImage object (the original, untouched image).
• public EzImage getNewImage()
  This returns the new EzImage object (the modified image).
• public void scratch()
  This method should apply artificial scratching of some kind to the image. Diagonal white lines would be fine, but feel free to be creative.
• public boolean filter(int radius)
  This method should apply the median filter described above, using square neighborhoods of the specified radius. A radius-1 neighborhood will be a 3-by-3 square, a radius-2 neighborhood will be 5-by-5, etc. This method should typically return true, but it should return false if the radius is less than 0.

Advice

• Remember that you want to do this only for gray images, so convert any images that you use to gray before calling these methods.
• The neighborhoods of pixels near the borders of the image will not be squares. Don't forget to build your neighborhood out of only those pixels that are within the boundaries of the image. Otherwise, you'll end up with those pesky ArrayIndexOutOfBoundsExceptions.
• Start early, ask questions if you have them, and have fun.