CS 355 Lab 6: Image Processing


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For this lab, you will implement the following basic image processing operations:
• Brightness adjustment
• Contrast adjustment
• Noise removal / blurring (uniform averaging)
• Noise removal (median filtering)
• Sharpening (unsharp masking)
• Edge detection (gradient magnitude)

You will be again given a shell to start with, which is an extension of the one you used for Lab 5. This is
solely so that when you’re done you can have all of the parts you did in one program. You will not be graded
on whether all the parts from Labs 1–3 or 5 work, so long as what you have integrates with the new image
processing operations.

The drawing of the image should be done behind anything drawn with the 2D drawing tools or 3D
rendering (if any). Think of the image as forming a backdrop that always stays behind the other drawing.

User Interface

In addition to the GUI elements from Labs 1–3 and 5, there is a new button that toggles display of the
background image layer, much like the toggle button for the 3D graphic rendering layer in Lab #5. There
are also new menu commands for the following operations:
• Load
• Save
• Brightness
• Contrast
• Blur (Uniform)
• Blur (Median)
• Sharpen
• Detect Edges

These menu commands, including any resulting dialog boxes, are handled by the shell. Your controller’s
interface will include methods for handling these operations based on parameters provided through these
dialog boxes.

The “Open image” menu command opens a file selection dialog box, allowing a user to select which file
to open.
The ‘Save” menu command saves whatever you have rendered to the drawing area. (This doesn’t require
you to do anything to implement—whatever you render to the Graphics2D object pass to your view
refresher will be saved as an image to disk.)

The “Brightness” menu command opens a dialog box allowing the user to enter the amount for the
adjustment. The brightness adjustment parameter will be a number in the range [−255, 255], with 0 (no
adjustment) as the default.
The “Contrast” menu command opens a dialog box allowing the user to enter the amount for adjustment.

The contrast adjustment parameter will be in the range [−100, 100], with 0 (no adjustment) as the default.
The remaining commands will not take any parameters and thus do not involve dialog boxes.

General Implementation

As mentioned already, you will be given a new shell to use. You should integrate into it all of the functionality from Lab #5, which is probably most easily done by using your previous model, view, and controller,
then adding to the view and controller the new methods necessary to implement the new interface. It is recommended that you first reproduce your Lab #5 functionality (or at least Lab #3) with the new shell using
stubs where necessary, then add the new functionality.

The model, view, and controller should be separate, as you did in Labs #1–3 and #5. Your controller
should maintain the 3D camera state, and the view should query your controller to get it for drawing, much
as you probably did for Lab #3 for zooming and scrolling.

For this lab the model should store the current image (if any) in addition to your 2D shape model code from
Lab #3 and the HouseModel from Lab #5. The model should store the current image as a new class that
contains the following information:
• The height and width of the image
• The pixel data for the image as a 2D array of int values
• Any other information you may need in order to perform the supported operations

All of the image-processing operations should be done in the model. You may choose to implement them
as methods of your image class (but be aware that some of these require creating other images as temporary
results). Another option that is often done is to create separate classes with methods that implement operations on the image. For each operation, the new image should replace the stored image so that subsequent
operations use the result of the current one.

All of the images we will use will be grayscale. (If you load a color image, the shell will automatically
convert it to gray.) Your intermediate values may be floating point or go outside the [0,255] range of the
image, but you should make sure to store only integer values clipped to this range.

You should implement the seven operations for this lab as follows. In addition, you should provide
methods for the viewer to ask the model for image’s height, width, and 2D array of int pixel values.

New Image
Replace the data stored in the model with that for the newly opened image.

Brightness Adjustment
The brightness adjustment will be in the range [-255,255] and is applied additively. If b is the the brightness
adjustment parameter, then the level operation applied is
s = r + b
where as used in class r denotes the input brightness and s denotes the output brightness.

Contrast Adjustment
Rather than a straight linear operation, we will use a mapping similar to what Photoshop does. In particular, the contrast will be in the range [-100,100] where 0 denotes no change, -100 denotes complete loss
of contrast, and 100 denotes maximum enhancement (though not quite thresholding). If c is the contrast
parameter, then the level operation applied is
s =

c + 100
100 4
(r − 128) + 128
Blurs the image using a 3 × 3 uniform averaging kernel.

Median Filter
Applies a median filter to the image using a 3 × 3 neighborhood.
Sharpens the image using an unsharp masking kernel with A = 2 (i.e., a 6 in the middle and -1s for the
four-connected neighbors, then divide by 2).

Edge Detection
Computes the gradient magnitude for the image by first applying Sobel kernels to the image then combining
the results into a gradient magnitude image. For the Sobel kernels, make sure to divide the result of the
convolution by 8 before using them for the gradient computations.

In addition to the event handlers your controller provided in Labs #1–3 and #5, you have seven new methods
to implement in the controller interface.
public void toggleBackgroundDisplay()

This should toggle off and on the display of the image layer, much like you did for the 3D rendering layer
in Lab #5.
public void doLoadImage(BufferedImage openImage)
The shell will open the file and verify that it is an image, then read it in and pass it to you as a BufferedImage.

(This is to save you from having to implement the I/O and image handling.) You should then use getRaster
to get the WriteableRaster from the BufferedImage, then use getPixels to get a 2D array of
int values for the pixels. Then pass this array to your model to store and use.

public void doChangeBrightness(int brightnessAmountNum)
Invokes the model’s code for applying brightness adjustment to the image stored in the model.
public void doChangeContrast(int contrastAmountNum)
Invokes the model’s code for applying contrast adjustment to the image stored in the model.
public void doUniformBlur()
Invokes the model’s code for blurring the image stored in the model.
public void doMedianBlur()
Invokes the model’s code for median filtering the image stored in the model.
public void doSharpen()
Invokes the model’s code for sharpening the image stored in the model.
public void doEdgeDetection()
Invokes the model’s code for applying edge detection to the image stored in the model.

When asked to draw the screen, your viewer should first draw the background image, then draw the 2D
shapes and the 3D rendering. Each of these should be drawn to the same Graphics2D object passed to
your view refresher.

To render the image to the Graphics2D object, the viewer should first query the model for size of the
image and a 2D array of int values for its pixels. The viewer should then create a new BufferedImage
of the correct size, making sure to set the ImageType to TYPE BYTE GRAY. Then use getRaster to get
this image’s WriteableRaster. Then use putPixels to put the pixels to the WriteableRaster
for the BufferedImage. Finally, draw the BufferImage to the 2048 × 2048 drawing area using
the graphic object’s drawImage method so that the center of the image corresponds to the center of the
drawing area. Make sure to set the graphic object’s AffineTransform to be the same as you use for the
other layers (the viewing transformation you added in Lab #3) so that the scrolling and zooming works as
in previous labs.

Submitting Your Lab
To submit this lab, again zip up your src directory to create a single new src.zip file, then submit that
through Learning Suite. If you need to add any special instructions, you can add them there in the notes
when you submit it.

This is tentative and may be adjusted up to or during grading, but it should give you a rough breakdown for
partial credit.
• Loading and displaying image (10 points)
• Brightness adjustment (5 points)
• Contrast adjustment (5 points)
• Uniform blurring (10 points)
• Median filtering (10 points)
• Sharpening (10 points)
• Edge detection (15 points)
• Otherwise correct behavior (5 points)
TOTAL: 70 points
Change Log
• November 20: draft specification release
• November 20: corrected typo in brightness/contrast adjustment equation (one subtraction should have
been addition)
• November 20: split brightness and contrast into two separate menu commands / operations (this
simplifies the GUI programming in the shell); added save command (no work required to implement)
• November 21: tweaked details to match shell code (menu labels, method names, etc.) and other small
revisions for clarity; added tentative rubric