近年來數位資訊與網路的發展迅速，數位多媒體在網際網路容易被下載、竄改與破壞，因此智慧財產權的保護變得更重要。大部分多媒體在儲存空間或傳送時間皆以壓縮位元串流的型式來儲存，因此本論文在資訊隱藏提出兩種新穎的資料隱藏技術，分別為資料隱藏於半色調影像與資料隱藏於灰階影像，尤其資料隱藏於灰階影像還能達到壓縮的效果。
首先，本論文提出複雜度適當的資料隱藏演算法來嵌入機密圖案至兩張或多張半色調影像，先前文獻未依據不同的變異數值添加不同雜訊的強度，在此可調式雜訊平衡錯誤擴散法提出的方法是根據區域變異數值，不同的變異數值使用品質-雜訊查表法與最佳化倍率來控制添加雜訊強度，實驗結果顯示本論文提出方法與先前文獻方法在維持相同影像品質效能下有較高的解碼率。
此外，本論文提出另一個資料隱藏方法在有序抖動區塊截斷編碼影像的位元平面可彈性嵌入不同的資料量，其中有序抖動用於抖動量化區塊截斷編碼影像來避免先前區塊截斷編碼影像造成令人厭煩的假邊與區塊效應。實驗結果顯示適當複雜度可彈性嵌入的容量具有客觀良好的影像品質，除了正確解碼率維持100%外，如有需要還可在解碼端將有序抖動原始區塊截斷編碼影像重建。

The digital information over Internet have been growing rapidly recently. Digital multimedia can easily be downloaded or manipulated and tampered intentionally. So the intellectual property protection becomes more important. Most multimedia is stored in compressed bit stream format to save the storage space or transmission time. This thesis proposes two novel techniques for data hiding, data hiding in halftoning images and data hiding in grayscale images, respectively. Notably, the proposed data hiding in grayscale images can also achieve compression benefit.
First, this thesis presents a reasonable computational complexity data hiding algorithm to embed secret pattern into two or more halftone images. The former approaches in the literature do not consider noise strength according to the local variance value. The proposed Adaptive Noise-Balanced Error Diffusion (ANBEDF) method employs the Quality-Noise Look Up Table (QNLUT) and the optimized multipliers to control the adaptive noise strength according to the local variance value. The experimental results show that higher decoding rate is available under the same image quality performance than former approaches in the literature.
Moreover, this thesis proposes another data hiding which can embed flexible amount of data in the bit map of an Ordered Dither Block Trumcation Coding(ODBTC)image, where the ordered dithering is used to dither the quantized BTC image to avoid the annoying false contour and blocking effect inherently existed in BTC image. Experimental results demonstrate that an objective good image quality image with flexible capacity and reasonable complexity is obtained. Moveover, the correct decoding rate of 100% is maintained, and the original host ODBTC image can also be reconstructed in the decoder when needed.

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