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Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation

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Abstract

Underwater images, which have low contrast and visibility as a result of selective attenuation based on the wavelength of the light passing through water, needs some corrections to extract meaningful information from them. In this paper, we aim to combine two different approaches; global and local contrast enhancement techniques, to obtain better visual quality while enhancing image contrasts on underwater images. While global technique (LDR) ensures the overall enhancement of the image, local technique (CLAHE) considers local brightness features of the image in RGB color space. The proposed method also applies local color correction on underwater image. While methods in the literature apply various approaches on the global histogram of channels, our method divides underwater image into non-overlapping sub-blocks and apply histogram equalization on them. The method uses HSV color space and especially S, V components for color correction. The results of the qualitative analysis show that it produces very good images, in contrast, color, and detail compared to other enhancement methods. The proposed method also decreases the effect of under- and over-enhanced areas and the blue-green effect on the output image. However, the visibility of the objects in the images are increased by color correction. For quantitative analysis, the proposed method produces the highest average value of entropy (7.83), EMEE (32.06), EME (40.97), average gradient (152.55), and Sobel count (130393) for 200 underwater images.

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Authors and Affiliations

  1. Computer Engineering Department, Karadeniz Technical University, Trabzon, Turkey

    Guzin Ulutas & Beste Ustubioglu

Authors
  1. Guzin Ulutas
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  2. Beste Ustubioglu
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Correspondence to Beste Ustubioglu.

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Appendix

Appendix

figure a

Image

 

Original

HE

ICM

UCM

CLAHS

CLAHE–Mix

CLAHE and Percentile

ICMRD

RAHIM

Proposed

Image 1

Entropy

7,23

5,98

7,63

7,26

7,36

7,52

7,56

7,88

7,67

7,88

EME

9,10

23,20

25,30

24,35

16,43

21,40

22,43

25,58

24,85

47,76

EMEE

0,57

4,94

6,04

4,69

1,47

2,47

2,73

9,53

5,27

41,91

Gradient

51,93

121,81

96,41

79,28

99,29

104.25

100,75

109,583

96,22

169,87

Sobel

14065

34114

29294

24623

32357

33557

32136

32694

31164

43952

Image 2

Entropy

6,12

5,49

7,04

6,77

6,27

6,92

6,76

7,25

7,52

7,78

EME

2,77

23,86

13,73

12,01

5,20

7,41

5,61

16,32

14,66

31,65

EMEE

0,13

5,37

2,16

1,48

0,28

0,47

0,33

5,66

1,72

10,06

Gradient

8,95

82,30

39,96

38,14

19,61

37,20

24,34

45

43,92

87,29

Sobel

39

24143

5108

3598

430

3547

1017

6200

5799

26228

Image 3

Entropy

7,43

5,98

7,68

7,22

7,33

7,53

7,65

7,88

7,70

7,89

EME

8,88

22,83

25,72

24,06

15,53

21,38

23,15

22,78

25,25

47,88

EMEE

0,55

4,62

5,70

4,35

1,35

2,59

2,84

7,69

6,17

45,87

Gradient

45

100,30

83,42

63,71

90,93

101,89

92,68

90,82

85,83

167,74

Sobel

11211

30713

25552

18913

29686

32751

29472

29005

27055

45534

Image 4

Entropy

7,16

5,95

7,26

6,79

7,46

7,65

7,49

7,87

7,64

7,87

EME

17,84

25,76

34,45

39,23

20,20

30,91

26,70

31,10

33,96

41

EMEE

1,72

7,35

14,36

17,43

2,37

6,38

3,84

12,53

11,71

33,05

Gradient

62,79

129,20

101,82

76,50

99,16

107,95

105,13

120,54

109,42

154

Sobel

14317

31233

22876

18315

25703

27156

26061

30167

27295

34603

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Ulutas, G., Ustubioglu, B. Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation. Multimed Tools Appl 80, 15067–15091 (2021). https://doi.org/10.1007/s11042-020-10426-2

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