Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8202
標題: 數位影像擷取裝置內建模糊推理與類神經網路之高效能自動白平衡演算法設計
Design of High-Performance Automatic White Balance Algorithms with Inherent Fuzzy Inference and Neural Networks for Digital Image Capture Devices
作者: 林韶華
Lin, Shao-Hua
關鍵字: White balance;白平衡;fuzzy system;single objective optimization;fuzzy neural network;模糊系統;單一目標最佳化方法;模糊類神經網路
出版社: 電機工程學系所
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摘要: 
自動白平衡在數位相機中扮演著很重要的角色。缺少自動白平衡,在低色溫下影像會偏向紅色,在高色溫下影像會偏向藍色。本篇論文提出兩種白平衡方法:最佳化方法及色溫估測法。最佳化方法將白平衡化為最佳化問題並解決;色溫估測法利用模糊類神經網路估測未知影像之色溫進而對該影像做修正,經實驗後發現這兩種方法都得到不錯的結果。

Auto white balance is an important process in digital camera or CCD camera. Without auto white balance, the image becomes reddish under low color temperature and becomes bluish under high color temperature. In this thesis, we propose optimization methods and light estimation method. The optimization methods formulate the auto white balance to three optimization problems and solve them. The light estimation method use two steps: (1) utilize fuzzy neural network to estimate the color temperature of an image; (2) apply scale factors to adjust the image. Our methods have good performance in the experiment.
URI: http://hdl.handle.net/11455/8202
其他識別: U0005-2008200801523900
Appears in Collections:電機工程學系所

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