Image enhancement. Image enhancement belongs to image preprocessing

Transcription

1 Image enhancement Image enhancement belongs to image preprocessing methods. Objective o image enhancement process the image (e.g. contrast improvement, image sharpening, ) so that it is better suited or urther processing or analysis P. Strumiłło, M. Strzelecki

2 Image enhancement Image enhancement methods are based on subjective image quality criteria. o objective mathematical criteria are used or optimizing processing results. subjective perception

3 Image enhancemet methods Point processing Spatial iltering Image colouring

4 Image enhancement Brightness J M M i j ( i, j) Contrast C M M i j [ ( i, j) J ] M, image dimensions (i,j) gray level value at (i,j)

5 Image histogram J94, C9 Image brightness and contrast inluence image subjective quality perception J, C47 J9, C38

6 Image histogram Image : array[..m,..] o byte; Hist : array[..l-] o longint;... imhist(i) Hist:; or i: to M do or j: to do Inc( Hist[ Image[i, j] ] );

7 Image histogram Source image Image histogram represents statistical distribution o image pixel brightnesses bright 5 dark

8 Linear gray scale transormation L- g m g(i,j) m (i,j) + d d g m ~ contrast d ~ brightness L- OUTPUT IMAGE SOURCE IMAGE POIT OPERATIO

9 MATLAB Demo image histogram

10 Histogram stretching g POIT OPERATIO? Gimadjust(F, [ MI MAX ], [g MI g MAX ]) M I M A X L- g(i,j) (i,j)< MI L- MAX - ((i,j)- MI ), MI (i,j) MAX MI L- (i,j)> MAX

11 Histogram stretching - example MI, MAX

12 Grayscale inversion L- g L- We can use look-up table to implement image point operations

13 onlinear grayscale transormation L- ln(x) g(i,j) T( (i,j)) g sqrt(x) x exp(x) g L- OUTPUT IMAGE SOURCE IMAGE Grayscale normalization! POIT OPERATIO

14 onlinear grayscale transormation L- x γ, γ< g Gimadjust(F, [ MI MAX ], [g MI g MAX ], γ) x γ, γ> L- correction

15 onlinear grayscale transormation - example Source image

16 onlinear grayscale transormation - example Tx 5 5 Tsqrt(x) 8 6 4

17 onlinear grayscale transormation - example Te x 5 5 Tlog(x) 5 5

18 onlinear grayscale transormation - algorithm! "!# "! $ % %!# $ % % $ & ' ($ % % ))) & ' * +& ',-+.& / /,-+. )))

19 onlinear grayscale transormation - algorithm / 3!! 4 5," ))$ % %.4 5 ))) 3 & " $ % %,3.& /3 3 & ' * +& ',-+.&,/,-+.. )))

20 Enhacement o a telescope moon image Tb log(ax)

21 Linear gray scale transormation m MR bit image d histogram Brightness/Contrast adjustment window Medical Image Processing, Analysis and Visualization (MIPAV) by Center or Inormation Technology, ver..9

22 Image ehancement by image averaging 5 ( i, j) ( i, j) + η( i j) g, contaminated by additive noise η(i,j) o zero average an variance σ η that is not correlated to the image / 5 g(i,j) 7 4 ση σ η

23 Image ehancement by image averaging + + k k k k j i n j i j i n j i j i g ), ( ), ( )], ( ), ( [ ), ( WARIG! grayscale range

24 oise variance in the averaged image: ( ) { } η η η σ σ η η η + η + η + + η η η η σ E E E E E k k p k p k k k k k k k Image ehancement by image averaging One can also show that the pick value o noise {n} is reduced by a actor o ater image averagings

25 Image averaging example & ' & $ Additive Gaussian noise & 8 & ' 9 Addison-Wesley Microscope image o a cell

26 Cumulative histogram ensions image M L i M k hist i histc o array hists o array hist histogram cumulative histc histogram image hist i k dim,,...,, ]) / [ ( ] [ ; [..55] : [..55] :, single longint;

27 Cumulative histogram Histogram Cumulative histogram

28 Histogram equalization Histogram equalization aims at obtaining uniorm statistical distribution o image gray levels (uniorm probability density unction) By histogram equalization one gets: contrast enhancement image normalization

29 Histogram equalization p () p (g) g /(L-) L- g L- p ()hist[]/m p g (g)/(l-)

30 ] [ ) ( ] [ ) ( ) ( ) (,,, ) (, ) ( ) ( ) ( histc L M i hist L i p L g,...,lg L g i p L g L g u L du L dh h p du u p dh h p i i i g g g Histogram equalization

31 Histogram equalization Cumulative histogram.5 g Equalized histogram Histogram g ( L ) histc[ ]

32 Cumulative histogram - algorithm 5," ))$ % %. 5," ))$ % %. ))),".&,". 3 & ' $ % %,3.&,3!'.:,3. )))

33 Histogram equalization Jhisteq(I) 5 5 5

34 Histogram equalization - example

35 MATLAB Demo intensity adjustment

36 Correction o nonuniorm illumination