Computer Graphics, Fall 99

Thomas Funkhouser

Assignment 1: Image Processing

Due: 10/03/99 at 11:59PM.

Overview

In this assignment you will create a simple image processing program. The operations that you implement will be mostly filters which take an input image, somehow process the image, and produce an output image.

Getting Started

You should use the code available at /u/cs426/1/, on the MECA machines, as a starting point for your assignment. We provide you with several files, but only one, image.c, needs to be changed.

• image.h: Defines the types and declares the functions for image processing.
• image.c Implements the functions declared in image.h.
• main.c Parses the command line arguments, and calls the appropriate image functions.
• bmp.h: Declares the functions to read and write Windows BMP files.
• bmp.c: Implements the functions declared in bmp.h.
• Makefile.nt A Makefile suitable for Windows NT platforms.
• Makefile.unix: A Makefile suitable for UNIX platforms.

Also, you can find test images at /u/cs426/1/images.

After you copy the provided files to your directory, the first thing to do is compile the program. If you are developing on a Windows NT machine, running Microsoft Visual C++, from the MS-DOS prompt, type:

% copy Makefile.nt Makefile 
% "c:\Program Files\Microsoft Visual Studio\VC98\Bin\vcvars32"
% nmake

If you are developing on a UNIX machine, type:

% copy Makefile.unix Makefile 
% make

In either case an executable called image will be created.

How the Program Works

The user interface for this assignment was kept to the simplest possible, so you can concentrate on the image processing issues. The program runs on the command line. It reads an image from the standard input, processes the image using the filters specified by the command line arguments, and writes the resulting image to the standard output. For example, to increase the brightness of the image in.bmp by 10%, and save the result in the image out.bmp, you would type:

% image -brightness 1.1 < in.bmp > out.bmp

For each available image filter there is a corresponding optional argument. To see the complete list of options, type:

% image -help

If you specify more than one option, the options are processed in the order that they are found. For example,

% image -contrast 0.8 -scale 0.5 0.5 < in.bmp > out.bmp

would first decrease the contrast of the input image by 20%, and then scale down the result by 50% in both x and y directions. Another way of doing the same thing would be

% image -contrast 0.8 | image -scale 0.5 0.5 < in.bmp > out.bmp

which uses pipes instead of multiple options per command line. The ability to use pipes can be used to avoid creating temporary files. For example,

% image -contrast 0.8 | image -scale 0.5 0.5 < in.bmp | xv -

does the same thing as the previous command, but it redirects the final output to be the input of xv, which simply shows you the result on the screen, without creating any temporary files in your directory.

Another advantage of this kind of interface is that you can combine different filters in shell scripts, and automate image processing steps, which can save you time.

What You Have to Do

The assignment is worth 15 points. The following is a list of features that you may implement. The number in front of the feature corresponds to how many points the feature is worth. The features in bold face are required. The other ones are optional.

• Random noise (1): Add noise to an image.
• Brighten (1): Individually scale the channels of an image.
• Contrast (1): Change the contrast of an image. See Graphica Obscura.
• Saturation (1): Change the saturation of an image. See Graphica Obscura.
• Quantize (1): Change the number of bits per channel of an image.
• Random dither (1) : Convert an image to a given number of bits per channel, using a random threshold.
• Composite (1): Composite one image with a second image, using a third image as a matte.
• Blur (2) : Blur an image by convolving it with a low pass filter.
• Edge detect (2): Detect edges in an image by convolving it with an edge detection kernel.
• Ordered dither (2): Convert an image to a given number of bits per channel, using a 4x4 ordered dithering matrix.
• Floyd-Steinberg dither (2): Convert an image to a given number of bits per channel, using dithering with error diffusion.
• Scale (3): Scale an image up or down by a real valued factor.
• Rotate (3): Rotate an image by a given angle.
• Fun (3): Warp an image using a filter of your choice. For inspiration, take a look at the effects available in programs like xv, PhotoShop, and Image Composer. (examples: fisheye, sine, bulge),
• Creating a composite image of yourself and a famous person (1).

For any feature that involves resampling, like scale and rotate, you have to provide three sampling methods: point sampling, bilinear sampling, and Gaussian sampling.

By implementing all the required features, you get 13 points. There are many ways to get more points:

• implementing optional features (as listed above),
• submitting images for the art contest (1), and
• winning the art contest (1).

For any image that you submit, you also have to submit the sequence of commands used to created the image, otherwise the image will not be considered valid.

It is possible to get more than 15 points. However, after 15 points, each point is divided by 2, and after 17 points, each point is divided by 4.

What to Submit

You should submit:

• the complete source code with a Makefile,
• the images (sources, masks, and final) for the composite feature,
• the images for the art contest, and
• a writeup.

The writeup should be a HTML document called assignment1.html which may include other documents or pictures. It should be brief, describing what you have implemented, what works and what doesn't, how you created the composite image, how you created the art contest images, and instructions on how to run the fun filters you have implemented.

Make sure the source code compile in the MECA workstations. If it doesn't, you will have to attend to a grading session with a TA, and your grade will suffer.

Always remember the late policy and the collaboration policy.

Hints

• There is a lot of functions to manipulate pixel components and pixels in image.[ch].   You may find them helpful while writing your filters.
• If you choose to develop on NT instead of Unix, you may prefer to create a project with the given source files, instead of using the given Makefile.nt.
• Check out the examples page, that describes each filter in more detail.
• Post questions to the pu.cs.426 newsgroup.
• Check out the submissions for the composite feature, fun filters, and art contest.
• These are the art constest winners.
• Stay tuned for more hints.

FAQ

• For the quantization function, can we safely assume that the image channels for input are always 8 bit and not any greater?
  • Yes.
• For the quantization function, should we assume that the number of bits to which we're quantizing is always a multiple of 3?
  • No. The parameter is the number of bits per channel, not per pixel.
• I get error messages and a core dump when the program tries to read in my bmp files. What should I do?
  • Make sure your files are 24-bit, uncompressed bitmaps. The provided code does not read any other kind of files. If you are using xv: right-click to open the xv controls window, then click on the 24/8 Bit menu-button, then select the 24-bit mode option. Alt-8 toggles between 8-bit and 24-bit mode
• When I run the program on NT, the output image is always black. What's wrong?
  • On Windows, NT, stdin and stdout are opened as text files, not as binary files. A new version of main.c that fixes this has been released.
• Stay tuned for more questions.

Announcements

• Thursday, 09/23
  • A new Makefile.nt with bug fixes was released.
• Sunday, 09/26
  • A new main.c with bug fixes was released.
• Wednesday, 09/29
  • A new main.c and a new Makefile with bug fixes were released.
  • More test images were released.
• Thursday, 09/30
  • A blue background (so you can take pictures of yourself for the composite feature) was setup at MECA.