電機資訊學院: 電子工程學研究所指導教授: 曹恆偉宋大成Sung, Da-ChengDa-ChengSung2017-03-062018-07-102017-03-062018-07-102016http://ntur.lib.ntu.edu.tw//handle/246246/276347影像感測器是數位相機中擷取影像的重要元件，要記錄每一個像素的紅、藍，綠三個顏色，就需要三個影像感測器，為了節省成本和空間，大部分數位相機只採用一個影像感測器，因此需要彩色濾波器陣列和彩色影像內插技術，彩色濾波陣列將紅、藍，綠三顏色過濾後，只通過其中一個顏色，經過影像感測器記錄後，再由彩色影像內插技術利用相鄰像素顏色將原來像素的紅、藍，綠三顏色還原，這個處理過程稱為彩色影像內插技術。 本論文主旨在設計和分析彩色影像內插演算法，研究著重在彩色影像內插技術中的二個部分，分別是邊緣偵測分類器和使用次波段合成技術。在本論文的第一部分，首先介紹彩色影像內插的研究背景和研究動機，然後回顧傳統彩色影像內插技術。傳統彩色影像內插技術依照使用的方法可以分成三類演算法：分別是無邊緣偵測演算法、邊緣偵測演算法及頻率相關演算法◦邊緣偵測演算法在彩色影像內插技術中是非常重要的一部分，因為當運用相鄰像素內插還原遺失的像素時，沿著邊緣內插或是跨過邊緣內插，結果會有相當大的差別，在本論文的第二部分將會介紹傳統邊緣偵測分類器和我們提出的小波轉換邊緣偵測分類器◦在彩色影像內插技術處理過程中，有兩個影響影像品質的關鍵因素，分別是拉鍊效應和色彩偏差效應，在本論文的第三部分，提出的小波轉換彩色影像內插技術，可以大幅降低拉鍊效應和色彩偏差效應，首先，提出的小波轉換彩色影像內插技術利用邊緣偵測方法，內插還原初始的遺失像素值，其次，再利用小波轉換後，不同色彩間的高頻次波段的高相關性，還原得到準確的內插遺失像素綠色色彩值，最後再運算更新紅色與藍色的高頻次波段以降低色彩偏差。 本論文提出了高效率的邊緣偵測分類器及小波轉換彩色影像內插技術,實驗結果顯示，提出的小波轉換彩色影像內插技術保留了邊緣的細節並且還原了高品質影像。Digital still cameras use image sensors to capture images. To reduce the size of digital still cameras, a single image sensor instead of three image sensors should be used. A single image sensor overlaid with a color filter array (CFA) that only captures one color channel at each pixel; thus, the other two missing color channels at each pixel must be reproduced from neighboring pixels. This procedure is known as CFA interpolation or demosaicking. The main goal of this thesis is to design and analyze algorithms of CFA interpolation. Our research focuses on two CFA interpolation systems: classifiers for edge detection and demosaicking by using subband synthesis. At the first part of this thesis, we introduce the background of CFA interpolation and the research motivation. Then, the traditional techniques of CFA interpolation are reviewed. They can be categorized into three groups which are non-edge-sensing algorithms, edge-sensing algorithms and frequency correlation algorithms. Classifiers for edge detection are important in CFA interpolation, since interpolating a missing pixel along an edge or across an edge can result in apparently different interpolation. In the second part of this thesis, classifiers for edge detection are introduced and a novel wavelet-based interpolation algorithm is presented to predict the direction of edges. In CFA interpolation process, there are two artefacts, i.e. zipper effect and false color artefacts may affect the CFA interpolation performance. In the third part of this thesis, a wavelet based CFA interpolation method is presented to reduce zipper effect and false color artefacts. First, an edge detection method is used to interpolate the initial missing color channels. Second, the high correlations between wavelet subbands of the different color channels are explored to obtain accurate green color values of the estimated green channel. Finally, the high-frequency subbands of red and blue channels are iteratively updated to reduce false color artefacts. In this dissertation, effective classifiers for edge detection and a wavelet based CFA interpolation algorithm are presented. Experimental results demonstrate that our proposed method can indeed preserve edges and restore images with high quality.3634897 bytesapplication/pdf論文公開時間: 2021/7/6論文使用權限: 同意有償授權(權利金給回饋學校)彩色影像內插法CFA interpolationthesis10.6342/NTU201600242http://ntur.lib.ntu.edu.tw/bitstream/246246/276347/1/ntu-105-D95943017-1.pdf