Image Hiding Based on Hybrid VQ Compression and Discrete Wavelet Transformation

在這個網路及多媒體技術發展迅速的數位化時代，於網路上傳輸重要資訊隨時有被竊取的危機。基於這個原因，許多研究學者紛紛投入資料隱藏的研究。資料隱藏主要方法是，將要傳輸的秘密資訊先藏入一張掩護影像中而產生一張偽裝影像，藉由傳輸這張偽裝影像將秘密資訊透過網路傳給接收方。針對數位影像的傳輸和儲存來說，向量量化(Vector Quantization, VQ)是一種很有效率的影像壓縮技術，其主要的優點是壓縮率很高、編碼/解碼處理容易以及具有區塊各自獨立的特性(即當某一個區塊損毀時，僅有該對應的區塊受損，其他區塊不會受到影響)。另一方面離散小波轉換(Discrete Wavelet Transformation, DWT)是一種將空間域影像轉成頻率域影像的技術，將影像由空間域轉為頻率域的好處是可以將影像分為不同程度重要性的資料，如此便能針對不同重要性的資料做適當的處理。本碩士論文提出一個結合VQ壓縮法及離散小波轉換之影像隱藏的技術。 結合VQ壓縮法及離散小波轉換之影像隱藏技術是一種具有抵抗性的影像隱藏方法。其主要的作法是，針對欲隱藏的灰階秘密影像先進行VQ壓縮，並提出一個訓練編碼簿的方法，使灰階秘密影像在加解密時能得到好的品質。接下來再對灰階掩護影像做一階離散小波轉換的運算，將秘密影像壓縮得到的索引值加密後分別藏入不同的重要頻帶。最後再對此影像做反小波轉換的運算，即產生一張灰階偽裝影像。最後，傳送方只需傳輸偽裝影像和兩把金鑰以及少數個用來分群的編碼字，接收方便可利用這些資訊來還原出秘密影像。當偽裝影像有些許破壞時，本論文也提出一個方法來修補秘密影像，提升秘密影像的還原品質。There are a lot of dangers to transfer important information in computer networks today. Thus, many researchers focus on the field of data hiding. The main method of data hiding is to embed the important information into a cover image. Then a stego-image is generated. By transferring the stego-image in computer networks, the important information is transferred to the receiver. Vector Quantization (VQ) compression is an effective compression method of digital images for the purpose of transmission and storage. The major advantages of VQ compression are that the compression rate is very high, the encoding and decoding are simple, and there is a feature that each block is independent (i.e. the other blocks are not destroyed if some of the blocks are destroyed.). On the other hand, Discrete Wavelet Transformation (DWT) is a method to transfer an image from spatial domain into frequency domain. The advantage of DWT is that an image is divided into several data with different importance. Thus, each kind of data can be processed in different methods. This thesis proposes a hybrid VQ compression and discrete wavelet transformation for image hiding. The proposed image hiding method is robust. The proposed method is to compress the gray-level secret image with VQ compression before the secret image is hidden. The proposed method proposes a method to train a codebook such that the quality of the secret image can be better in encryption and decryption. Then the compressed data of the gray-level secret image is encrypted before embedding into the DWT coefficients of the cover image. After inverse DWT calculating, the stego-image is generated. Finally, the sender only needs to transfer the stego-image, two keys, and a set of the initial codewords to the receivers. The secret image can be rebuilt with the received information. If the stego-image is destroyed, the proposed method can also recover the secret image partially.Chapter 1 Introduction 1 Chapter 2 Related works 6 2.1 VQ compression 6 2.2 DWT 9 Chapter 3 The proposed method 12 3.1 Encryption process 13 3.1.1 Gray-level secret image compression procedure 14 3.1.2 Data hiding processing 18 3.2 Decryption process 22 Chapter 4 Experimental results 24 Chapter 5 Conclusions 33 Chapter 6 References 3