碩士 / 國立臺灣大學 / 工程科學及海洋工程學研究所 / 106 / In the field of undersea related research, underwater vehicles usually carry a visual system that captures various images of interested creatures, minerals and monitors environmental conditions. Unfortunately, the captured images often have serious color distortion and poor visibility problems. This is because that underwater images are usually affected by the turbid water medium and floating particles existed in the water. Three different problems of attenuation, absorption, and scattering happen while light propagates in the water. These phenomena cause low contrast in underwater images. Furthermore, the quantity of attenuation is associated with the wavelength of light . In this thesis, we simplifies the optical model and proposes an effective algorithm to recover underwater images. First, we compute the background light and transmission using two different algorithms. Based on the fusion principle and specific weights in between, we can obtain better the background light and transmission after fusion. The visibility of scene is compensated by the object-camera distance to recover the color of the background and objects. Subsequently, by realizing the physical property of the point spread function, we adopted a low-pass filter to deblur the image by deconvolution. Finally, we equalize the color mean in each channel to balance the color. Comparing with many existing methods, our method demonstrated better restoration results and visual quality.
| Identifer | oai:union.ndltd.org:TW/106NTU05345046 |
| Date | January 2018 |
| Creators | Jun-Qi Li, 李俊棋 |
| Contributors | 張恆華 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 60 |
Page generated in 0.0016 seconds