利用浮水印技術於影像破壞區域之偵測與修補

常見的影像修復技術，主要的瓶頸在於邊緣的修復。為了解決修補法在確定影像邊緣上的難題，還有修補時，提升正確性，本文提出一利用浮水印技術用於影像破壞區域之偵測與修補。我們將原圖之重要邊緣抽出，視為強健型浮水印，再嵌入於原圖做一階小波之後的1 LL 位置中，以作為修補比對之參考。本技術亦嵌入一易碎型浮水印，修復系統可藉由抽取易碎型浮水印，自動偵測待測影像之破壞區域，同時利用抽取出之強健型浮水印(重要邊緣)，依照其重要邊緣紋理，進行階層式修補，包含區塊修補法及結構擴展法。但是同時嵌入兩個浮水印，又要提升嵌入之後的影像PSNR 值，是很困難的。所以我們利用小波轉換與VQ 結合，來減少需要嵌入的資料量。由實驗結果可證實，嵌入浮水印之後，測試影像仍然不易察覺的優點，受破壞之後，本技術可自動偵測破壞區域，並成功修補之。

關鍵字

小波轉換；浮水印；向量量化編碼；影像修補

並列摘要

In image completion and inpainting technique,the key issue is edge restoration. In order to resolve the image inpainting problem in the object edge and to enhance the accuracy of the original image during repairing, we presents a multi-purpose watermarking technique to repair image automatically. We use the edge of the original image as the robust watermark and embed it into the lower frequency band as the reference for repairing defected area. We also embedde a fragile watermark into image. By extracting the fragile watermarking, the repair system can detect the defected area automatically. Meanwhile, we utilize the extracted robust watermarking, followed by the texture of object edge, to repair the image block and edge of image. It is difficult to insert two watermarks and to achieve high Peak Signal to Noise Ratio, so we use the Discrete Wavelet Transform and Vector Quantization techniques to minimize the embedded data. According to the experimental results, the embedded watermark is invisible in the test image. When the test image was attacked, this technology can detect the large defected area or complicated defected area and repair it automatically.

並列關鍵字

Wavelet transform ； Watermarking ； Vector Quantization ； Image inpainting

參考文獻

with Structure Propagation,” ACM Transactions on Graphics ,

Image Restoration” IEEE Transactions on Image Processing, VOL.

[3] R. M. Gray, “Vector Quantization,” IEEE Transactions on Acoustics,

[5] John F. Canny. “A computational approach to edge detection,” IEEE

Transactions on Pattern Analysis and Machine Intelligence,

國際替代計量

利用浮水印技術於影像破壞區域之偵測與修補

全文下載

主題瀏覽