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研究生(外文):Chia-Yang Cheng
論文名稱(外文):Underwater Image Restoration by Red-Dark Channel Prior and Point Spread Function Deconvolution
外文關鍵詞:underwater imageimage restorationred-dark channel priorpoint spread function deconvolutionwavelength and depth compensation
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In the field of undersea research, underwater vehicles usually carry camera systems for recording. The captured images and videos often have two undesired characteristics: color distortion and low visibility. This is because that the light is exponentially attenuated while penetrating through water. Furthermore, the quantity of attenuation is associated with the wavelength of light spectrum. This thesis simplifies the Jaffe-McGlamery optical model and proposes an effective algorithm to recover underwater images. In our approach, a red-dark channel prior was defined and derived to estimate the background light and the transmission. The visibility of scene was compensated by the object-camera distance to recover the color of the background and objects. Subsequently, by analyzing the physical property of the point spread function, we developed a simple but efficient low-pass filter to deblur the image by deconvolution. Finally, we used the relationship between the radiance above the sea surface and the absorption coefficient to correct the color distortion. A wide variety of underwater images with different scenarios were used for the experiments. The experimental results show that the proposed algorithm effectively recovered underwater images while eliminating the influence of absorption and scattering. Comparing with many existing methods, the proposed framework provided more natural restoration results. We believe that this new restoration algorithm is promising in many underwater image processing applications.

Acknowledgements i
中文摘要 ii
Contents iv
List of figures vi
List of tables x
List of symbols xi
1.1 Background 1
1.2 Motivation 2
1.3 Organization of the thesis 3
2.1 Color model 4
2.1.1 RGB color space 4
2.1.2 HSI color space 5
2.2 Image domain 7
2.2.1 Spatial domain 7
2.2.2 Frequency domain 7
2.3 Edge preserving 8
2.4 Blind deconvolution 9
2.5 Nelder-Mead optimization 10
2.6 Underwater optical model 12
2.6.1 Absorption 13
2.6.2 Scattering 13
2.6.3 Direct light 15
2.6.4 Forward scatter 15
2.6.5 Back scatter 16
2.7 Underwater image processing 16
3.1 Simplified optical model 22
3.2 Red-dark channel prior 24
3.2.1 Background light estimation 25
3.2.2 Transmission estimation 26
3.3 Point spread function deconvolution 31
3.4 Transmission compensation 33
3.5 Color compensation 34
4.1 Color evaluation 36
4.2 Visibility evaluation 44
4.3 Recovery results 56
4.4 Applications 63
References 69

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