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Digital Image Processing Contrast Enhancement: Part I

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Presentation on theme: "Digital Image Processing Contrast Enhancement: Part I"— Presentation transcript:

1 Digital Image Processing Contrast Enhancement: Part I

2 Contrast Enhancement Contrast Stretching: improves the contrast in an image by stretching the range of intensity values to span a desired range of values.

3 Converts to black & white
Linear Part contributes to the contrast stretching © 2002 R. C. Gonzalez & R. E. Woods

4 k: number of bits used to represent each pixel
Some basic grey-level transformation functions used for contrast enhancement L=2k k: number of bits used to represent each pixel © 2002 R. C. Gonzalez & R. E. Woods

5 Image Negatives s= (L-1)-r
s is the pixel value of the output image and r is the pixel value of the input image. (left) Original digital mammogram. (right) Negative image obtained using the negative transformation © 2002 R. C. Gonzalez & R. E. Woods

6 Logarithmic Transformations
s= c log(1+r) s is the pixel value of the output image and r is the pixel value of the input image. (left) Fourier spectrum of Barbara’s image. (right) Result of applying the log transformation

7 Logarithmic Transformations
s= c rγ s is the pixel value of the output image and r is the pixel value of the input image. (γ ≥ 0 and 0 ≤ r ≤ 1) Plots for various values of γ (c=1) © 2002 R. C. Gonzalez & R. E. Woods

8 Logarithmic Transformations
b c d (a) original image. (b) γ = (c) γ = (d) γ = 0.7.

9 Piecewise-Linear Transformations
An example of piecewise linear transformation function © 2002 R. C. Gonzalez & R. E. Woods

10 Piecewise-Linear Transformations Other pixel values are darkened
grey-level slicing Pixel values between [A,B] are highlighted Other pixel values are preserved Other pixel values are darkened © 2002 R. C. Gonzalez & R. E. Woods

11 Piecewise-Linear Transformations
Bit Plane slicing An 8-bit fractal image © 2002 R. C. Gonzalez & R. E. Woods

12 Piecewise-Linear Transformations
Bit Plane slicing MSB LSB © 2002 R. C. Gonzalez & R. E. Woods

13 Histogram Processing Histogram : is the discrete function h(rk)=nk , where rk is the kth gray level in the range of [0, L-1] and nk is the number of pixels having gray level rk. Normalized histogram : is p(rk)=nk/n, for k=0,1,…,L-1 and p(rk) can be considered to give an estimate of the probability of occurrence of ray level rk.

14 Histogram of 4 basic grey-level characteristics
Dark image Bright image © 2002 R. C. Gonzalez & R. E. Woods

15 Histogram of 4 basic grey-level characteristics
Low contrast image High contrast image © 2002 R. C. Gonzalez & R. E. Woods

16 Summary We have looked at: What is contrast stretching?
What are different transformations? What is histogram and histogram processing? Next time we will talk about more on contrast stretching by using other techniques


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