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