[SOLVED] NCTU-IP Project 1

Your first task is to enhance the supplied images using techniques of contrast adjustment, noise reduction, color correction, and so on. There are 6 images supplied (5 regular photos, and one CT). They might not need the same kind of processing. As a result, you should write your processing techniques as modules so that you can try different combinations or parameters for different images. Try to do your best.

Note: For the CT image, you can only do noise reduction. No contrast or color adjustments here.

You can use either MATLAB, C/C++, or Python 3.x for the project. Regarding the restriction on toolbox/library usage:

You CAN use toolbox/library functions for:
 Image reading, writing, and display.
 Color space conversion.
 Matrix operations not specific to images.
You CAN NOT use toolbox/library functions for:  Image resizing.

 Intensity transformations.
 Histogram computation.
 Spatial filtering. (This includes functions for doing correlation, convolution, template matching, etc.) If you’re not sure about whether something can be used or not, ask the instructor.

About the submission:

•   Submit your report (as a single PDF file) through New E3.
•   Regarding the content of the report:
  1. The main text (max. 15 pages, not counting the code listing) should include the following sections: – Introduction / Objectives
     – A review of the methods you have used (be concise)
     – A explanation of the experiments you have done, and the results.

     – Discussions: Your observations, interpretations of results, and remaining questions.

  2. The report should be typed single-spaced, with 12-point font size.

  3. Include the program code listing at the end of your report, starting from a new page as a separate

  section.

•   Do not submit files in ZIP or RAR or other compressed forms. Do not submit program codes in separate

  files.

  The grade of each project is based on the following:
   The amount of effort you put in.
   Quality of your report (organization, clarity, completeness, depth).

 Quality of your outputs.
 Quality of your code (correctness, efficiency, clarity, documentation).

Other notes:
 Late submission: 10% deduction per day, up to until the submission is closed (usually one week from the

due date).

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Some notes about processing speed:
 Separable spatial filters.
 Using lookup tables for intensity transformations.  Vectorization, if you’re using MATLAB or Python.