臺灣博碩士論文加值系統

在本論文中，我們將一張影像分成我們有興趣的部分(ROI)，及背景部分(BG)，利用離散餘旋演算法取出影像的低頻係數，然後將有興趣部分的低頻係數以浮水印的方式藏入原影像的背景中，當影像在有限頻寬或即時系統中遭受干擾而錯誤時，可利用錯誤隱藏的技術將原影像回復使人眼無法發覺。所以，ROI 部分擁有非常強的抗破壞性，即使整張影像的 ROI 部分都損壞，也可藉由藏在背景中的資訊，來修補 ROI 部分；至於 BG 的部分，則以傳統的錯誤隱藏技術來修補遺失的影像。在影像遭受大量錯誤時，ROI利用 BG 資訊回復影像，但因 BG 遭到大量損毀，以至於無法正確的回復 ROI，在這情況下，我們必須對影像再做後處理，來達到錯誤隱藏的效果。

雖然我們在前處理時預先在 BG 藏入 ROI 的特徵資訊，然而在人眼無法察覺，及不破壞影像的前提下，完成我們的演算法。影像中我們有興趣的部分,具有良好的強韌性，可抵抗因網路傳送錯誤所造成的影像破壞。實驗結果顯示，在前處理時,我們可得到一張失真非常少的影像，而錯誤隱藏完後，可以得到一張看起來無損壞的影像和非常高的 PSNR 值。和傳統的方法比較，我們強調 ROI 的強韌性。本方法美中不足的地方，在影像於高錯誤率中，無法正確地回復 ROI，然而這種情況是非常少見的，即使是傳統的錯誤隱藏法也無法回復這種高錯誤率的影像。

In this thesis, an image is divided into two parts, region of interest (ROI) and background (BG). The discrete cosine transform is utilized to extract low frequency coefficients of an image. The coefficients of ROI are embedded to BG by watermarking technique. When errors occur in limited channel or real time system, they can be recovered by error concealment technique. Even if all ROI are damaged, the information of ROI embedding to BG can be extracted to reconstruct ROI. Therefore, ROI is very robust to congestion channel. As for BG, the traditional error concealment technique is used. When an image suffers a great deal of errors, ROI can be recovered by extracting information from BG. If BG suffers too many serious errors to recover ROI correctly, the postprocess is necessary.

Although ROI coefficients are embedded into BG in advance, it is invisible to the human eyes and doesn’t destroy the image. Simulation results show the original image is only a little bit distortion after embedding ROI coefficients. Finishing error concealment process, the reconstructed image has high visual quality and PSNR value. To compare with traditional techniques, the proposed technique emphasizes robustness of ROI. The proposed technique cannot recover ROI correctly when an image with high damage. Under the circumstance of high error rate, traditional techniques cannot handle, either.

Chapter 1 Introduction
1.1 Problem formulation
1.2 Problem solution
1.3 Thesis organization
Chapter 2 Overview of Basic Techniques
2.1 Overview of JPEG
2.1.1 Introduction to JPEG
2.1.2 JPEG compression technique
2.1.3 Architecture of JPEG
2.1.4 Discrete cosine transform
2.2 Overview of error concealment
2.2.1 Introduction to error concealment
2.2.2 Category of error concealment
2.3 Overview of digital watermarking
2.3.1 Introduction to digital watermarking
2.3.2 Types of watermarking
Chapter 3 Related Works
3.1 Error concealment approach
3.2 Fragile watermarking approach
3.3 Transmission errors over network
3.3.1 Effect of transmission errors in JPEG
3.3.2 Solution of error propagation
Chapter 4 The Proposed Technique
4.1 The architecture of proposed technique
4.2 Preprocess
4.2.1 Region-of-interest
4.2.2 Image randomization
4.2.3 Generating ROI coefficients
4.2.4 Embedding ROI coefficients into BG
4.2.5 Embedding authentication codes
4.3 Error concealment process
4.3.1 Error detection
4.3.2 Extracting the embedded information
4.3.3 Recovery
4.4 Postprocess
Chapter 5 Simulation Results
5.1 The general test
5.1.1 Lena image test
5.1.2 Barbara image test
5.1.3 F16 image test
5.2 Embedding coefficients test
5.2.1 Zelda image test
5.2.2 Lena image test
5.3 ROI selecting test
5.3.1 The body of F16
5.3.2 The tail of F16
5.3.3 The airframe of F16
5.4 Comparison between BNM and the proposed technique
Chapter 6 Conclusion
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