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Underwater Image Enhancement: A Comprehensive Study of Techniques and Applications, Thesis of Computer Science

research work uploded of pdf formate

Typology: Thesis

2019/2020

Uploaded on 02/17/2023

anuradha-vashishtha
anuradha-vashishtha 🇮🇳

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LIST OF FIGURES
Figure
No.
Figure
Caption
Page
No.
1.1.
Underwater scene of light propagation.
3
1.2.
Penetration of light with different wavelengths in the ocean.
3
1.3.
(a) Simplified image formation model. (b)(f) Examples of
underwater images having different underwater color tones.
5
1.4.
An Example of Nature Image.
6
1.5.
Binary Images.
7
1.6.
Gray scale images.
8
1.7.
Color Image.
9
1.8.
Steps of Image Processing.
10
1.9.
Example of Image restorations.
11
1.10.
The components of underwater optical imaging and color
appearance underwater.
14
1.11.
Methodology for an underwater image enhancement method
16
3.1.
Flow diagram of the proposed methodology.
30
4.1.
Dataset Images.
34
4.2.
Execution steps of proposed Methodology.
35
4.3.
Qualitative picture comparison shown in Fig. 2.(a) initial
underwater picture (b) Result of haze reduction (c) Result of
salience weighted map (d) Result of CAP (e) Result of
transmission estimate (f) Result of DCP (g) suggested contrast
stretching lead.
35
4.4.
image (a) 2.jpeg, image (b) 5.jpeg, image (c) 3.jpeg, image (d)
4.jpeg, and image (e) 6.jpeg, has been used in research work
which shows the different techniques used in the proposed
methodology.
36
4.5.
The visual output images after applying proposed techniques
on Dataset.
37
4.6.
Graph plot of UCQI & PCQI.
38
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LIST OF FIGURES

Figure No. Figure Caption Page No. 1.1. Underwater scene of light propagation. 3 1.2. Penetration of light with different wavelengths in the ocean. 3 1.3. (a) Simplified image formation model. (b)–(f) Examples of underwater images having different underwater color tones.

    1. An Example of Nature Image. 6
    1. Binary Images. 7
    1. Gray scale images. 8
    1. Color Image. 9
    1. Steps of Image Processing. 10
    1. Example of Image restorations. 11
    1. The components of underwater optical imaging and color appearance underwater.

1.1 1. Methodology for an underwater image enhancement method 16 3.1. Flow diagram of the proposed methodology. 30 4 .1. Dataset Images. 34 4 .2. Execution steps of proposed Methodology. 35 4 .3. Qualitative picture comparison shown in Fig. 2.(a) initial underwater picture (b) Result of haze reduction (c) Result of salience weighted map (d) Result of CAP (e) Result of transmission estimate (f) Result of DCP (g) suggested contrast stretching lead.

4 .4. image (a) 2.jpeg, image (b) 5.jpeg, image (c) 3.jpeg, image (d) 4.jpeg, and image (e) 6.jpeg, has been used in research work which shows the different techniques used in the proposed methodology.

4 .5. (^) The visual output images after applying proposed techniques on Dataset.

4 .6. Graph plot of UCQI & PCQI. 38

LIST OF TABLES

Table No. Table Caption Page No. 5 .1. Comparison of Base and Propose of UCIQE and PCQI.

ABSTRACT

This thesis deals with a technique of improving the quality of the underwater picture. In marine research, underwater images are a mandatory topic. Due to the characteristics of water and its impurities, the underwater picture quality is poor. Water features cause light to attenuate through the water medium, resulting in diminishing color in low contrast, blur, inhomogeneous lighting, and underwater picture. The Underwater pictures are helpless against the impact of low contrast and color casting due to the existence of dust particles in the water medium. This thesis suggests a method for improving the quality of the underwater picture. We suggest an underwater image restoration method to enhance the visual quality of the underwater image. The method of contrast stretching is used to remove the haze in the underwater image. It relies on the main perception of most neighboring’s patches in haze-free underwater images containing a few pixels in no less than one color channel with small intensities. However, previous color attenuation is amazing for removing fog from a single hazy image input. The goal is to improve contrasting underwater pictures while maintaining the brightness of the picture. The techniques suggested were tested using several underwater pictures and improved visual quality.