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The ICE Tool

The ICE Tool. Feng Wen Qi Yuan Kin Wah Leung. Presentation Overview. Project goal Interactive GUI Introduce image enhancement techniques Integration with Matlab ™ Implementation of image enhancement techniques Potential advancement of ICE tool. ICE Tool. What is ICE tool?

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The ICE Tool

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  1. The ICE Tool Feng Wen Qi Yuan Kin Wah Leung

  2. Presentation Overview • Project goal • Interactive GUI • Introduce image enhancement techniques • Integration with Matlab™ • Implementation of image enhancement techniques • Potential advancement of ICE tool

  3. ICE Tool What is ICE tool? • ICE = Image Contrast Enhancement • Capable of executing various image enhancement techniques • Provides easy to use interface • Can be altered according to desire needs if necessary

  4. Project Goal • To implement an interactive GUI capable of enhancing images • Research image enhancement techniques • Programming an interactive GUI • Integrating with Matlab™ libraries • Implementing image enhancement functions • make sure functions performed correctly

  5. Interactive GUI • The Interactive GUI (graphic user interface) • As user friendly as possible • Created using Java™ • - A programming language from Sun Microsystems • - Provides great system portability • Created as a Java™ frame application • GUI features • Ability to load and save desired images • Displays original and modified image on the same panel • Easy menu bar browsing

  6. GUI Features • Ability to load and save image • Ability to display both original and modified image on same screen

  7. GUI Features (cont…) • Easy toolbar browsing • Combines simple image enhancement methods

  8. Image Enhancement Techniques • Contrast Enhancement • Histogram equalization - Image quality can be improved by altering histogram - Calculates the ideal transformation from the histogram of the image - All gray levels used has a tendency to enhance image contrast Transformation Function: T(f ) can be calculated from the following relation:

  9. Image Enhancement Techniques (cont…) • Noise Removal Filter – removes dots or speckles on image (equivalent of low-pass filtering) • Average Filter (Mean) • - Replace each pixel by the average of the window area pixels • - Has the effect of smoothing image • - Larger window size removes noise more effectively while • - At the expense of blurring the details • Median Filter - Replace each pixel by the median of the window area pixels - More effective against impulse noise (aka salt and pepper) - Can retain details and edges better than averaging filter

  10. Image Enhancement Techniques (cont…) • Deblurring • Wiener Deblurring - Generalized inverse filter - Effective when information regarding frequency characteristics are known, at least to a degree • Lucy-Richardson • - Effective when the PSF (point-spread function) is know but little information is available for the noise • Sharpening • Enhances details and edges • Line structures can be obtain by applying high-pass filter

  11. Integration With Matlab™ • Benefits • Allows the access of the large Matlab™ function library - The Matlab™ math function library - The Matlab™ image processing function library • Integration process • Use of an software engine to link Matlab ™ and Java ™ GUI together • Implement the functions to the appropriate buttons

  12. Integration With Matlab™ • Incorporate with JMatLink • A Java engine capable of linking Java ™ applications and Matlab ™ - Use of native methods, no source code need to be changed - Created by Stefan Muller http://www.held-mueller.de/JMatLink/ • Edit autoexec.bat to set path to Matlab ™ and Java ™

  13. Image Enhancement Implementation • Research Matlab ™ code • Must know the codes for executing all of the image enhancement techniques • Ex: for histogram equalization I = imread(‘abc.jpg’); J = histeq( I ); • Implement the code to the Java ™ interface buttons • Every component assigned the appropriate Matlab ™ code • Press of buttons send Java ™ code to Matlab ™for execution

  14. Image Enhancement Implementation (cont…)

  15. Summary • Successfully creating an functional interactive GUI using Java • Java was integrated with Matlab™ through JMatLink • The Matlab™ code was associated with every button in GUI • Additional features and improvements can be made

  16. Future Advancement of ICE Tool • Try to make it a standalone application without Matlab™ • Addition of more image enhancement techniques • Addition of more features such as help documentation, zoom, etc • Package into an easy to install application

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