Presentation on Pseudo Color Image Processing on X-ray images, Medical images, NV images
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Transcript of Presentation on Pseudo Color Image Processing on X-ray images, Medical images, NV images
Pseudo Color ImageProcessing
On X-Rays
By Jaydip Fadadu(08BEC24) Kuldip Gor(08BEC030)
Guided ByProf. Tanish Zaveri
1. Night Vision Images2. Weapon detection in Luggage Scanning
@ airport3. Bio-Medical Images
Area Of working
What is Pseudo coloring? Why it is required? Human Eye Perception Current Scenario @ airport for luggage
scanning, Medical.
Pseudo Coloring
I to (R,G,B) R(x, y) = PR[I(x, y)]
G(x, y) = PG[I(x, y)]B(x, y) = PB[I(x, y)]
I(x, y) ⇒ {PR,PG,PB} ⇒ {R,G,B} ⇒ C(x,y)
Color Transform
Pseudo coloring of Night Vision Images
Block Diagram
Simulation Result
X-Ray Image
Contrast Stretch
Salt & Pepper Noise
Removal
Color Conversion
Enhanced Color Image
Simple Block Diagram of
Pseudo Coloring
Gray image is converted into Color Image Various Methods
1. Hot2. Jet3. Rainbow 4. HSI Based
Color Conversion
HOT coloring
JET coloring
RAINBOW coloring
HSI based coloring
Simulation Results of
Various Coloring Technique
1
2
3
4
5
6
Proposed Methodbased on
LOOK UP TABLE designed from
WARM color scale
X-Ray Image
Contrast Stretch Using Intensity Adjust
Warm Color Map
Enhanced Color Image
Adaptive Histogram Equalization
Noise Removal Using 2D-Median Filter
Look Up Table
Enhanced Gray Scale Image
Color Conversion Using Look Up Table
Detailed Block Diagram
WARM coloring
Simulation Results of
Proposed Method
1
2
3
4
5
6
Comparison based on
Colorfullness Metric
COLORFULLNESS METRIC
HOT JET HSI RAINBOW PROPOSED
1 165.82 0.8937 0.989 0.3512 76.3414
2 159.18 0.8947 0.9973 0.3512 73.7114
3 171.64 0.9241 0.8892 0.3512 73.7709
4 185.31 0.9396 0.9736 0.3512 81.549
5 156.77 0.811 0.7456 0.3512 78.31356 210.2 1.073 0.8602 0.3512 87.2228
ENTROPY
NO HOT JET HSI RAINBOW PROPOSED1 0.9734 3.607 5.4859 6.4439 5.7722 0.6764 3.5149 5.5525 6.4578 5.54013 0.7389 3.6231 5.5841 6.5618 5.58394 0.7643 3.8605 5.5473 6.443 5.54795 0.6358 3.5244 5.7071 6.9876 5.69246 1.5171 3.6661 5.4594 5.9877 5.7758
Comparison based on Entropy
Simulation results show the coloring of the gray images enhances the visibility of images and one can extraxt the information more easily. The entropy and colorfulness metric also shows the same.
Proposed method gives optimum output.
Conclusion
1) Andreas Koschan and Mongi Abidi, "Digital Color Image Processing," A John Willy & Sons, INC., Publication, Hoboken, New Jersey.
2) Rafael C. Gonzalez and Rechard E. Woods, “Digital Image Processing” Prentice Hall, New Jersey.
3) Tanish Zaveri, Mukesh Zaveri, Ishit Makwana and Harshit Mehta,“ An Optimized Region-based Color Transfer Method for Night Vision Application”.
4) Toet. Natural color mapping for multiband nightvision imagenary. Information Fusion, vol. 4(3), pp. 155-166, 2003.
5) Besma R. Abidi, Senior Member, IEEE, Yue Zheng, Andrei V. Gribok, and Mongi A. Abidi, Member, IEEE. “Improving Weapon Detection in Single Energy X-Ray Images Through Pseudocoloring” Ieee transactions on systems, man, and cybernetics—part c: applications and Reviews, vol. 36, no. 6, pp. 784-796, November 2006.
References
THANK YOU