近年來，高影像品質和高效能的壓縮比率是在多媒體壓縮系統裡的最重要的問題。而且，圖像完整驗證和版權保護在數位生活裡變得越來越必要。本論文將針對多媒體系統中四種重要的議題探討，分別為小波式影像壓縮、半色調影像處理、加速動態影像壓縮、及影像浮水印。在第一項議題研究裡，我們提出一個根據硬體實作上的需要，適當修改的階層式集合分割影像壓縮技術(SPIHT)編碼器並提高其硬體實現效率。階層式集合分割影像壓縮技術(SPIHT)是一種基於離散小波轉換的高效率影像壓縮技術。雖然它的壓縮效率比JPEG2000所採用的最佳方式切割的崁入式區塊編碼技術(EBCOT)稍差，但SPIHT是直接編碼影像的程序並且不需要須事先儲存的表格。這優點使得SPIHT更適合應用於低成本的硬體應用上。我們針對SPIHT演算法修改的部分，包括係數掃描過程的簡化和固定記憶體配置方式，係數掃描過程的簡化是針對小波係數的索引方式，利用一維的位置索引方式代替原先二為位置索引，而固定記憶體配置方式是將原先使用於SPIHT的動態配置方法改成資料列表的方式。雖然影像失真有些微的增加，但這些修改會讓SPIHT在硬體實作上變得更容易。
在第二項議題研究裡，我們提出基於類神經網路混合數位影像的半色調(Halftoning)和反轉半色調(Inverse Halftoning)回復連續影像的演算法。在此演算法中，半色調影像是由一階層類神經網路邏輯(SLPNN)所建立，此外，此半色調影像所對應的連續色調影像是由半徑式基底函數類神經網路 (RBFNN)所重建。這合併訓練程序同時產生半色調影像和其所對應的連續色調影像。利用我們所提出的演算法所取得的連續色調影像的峰值雜訊比(PSNR)效能和視覺影像品質，已與目前文獻上著名的反轉半色調方法相比較。並且本演算法所產生的半色調影像也比利用現存著名的擴散網紋半色調演算法所產生的結果在視覺上有更好的表現。
在第三項議題研究裡，我們提出一個加速完成H.264/AVC編碼壓縮的演算法，是利用其主要在執行眾多內部預測模式或外部預測模式之前，先行評估適當預測模式發生之可能性並省去部分模式的檢驗，即可先一步的將所需壓縮時間。在碼率失真最佳化H.264/AVC(縮寫為H.264/RDO)編碼器中，最佳的運算模式是由最小的Lagrange代價所決定，這是基於在計算壓縮率與失真代價之後，同時考慮可能的失真和所需的編碼位元數。H.264/RDO編碼器可以達到很好的壓縮率和影像失真之間的平衡，但同時需要許多額外的計算時間。我們所提出的方法稱為兩階層編碼模式決策演算法(TSMD)，這方法將暫停一編碼區塊所不需要的模式，並且只執行可能成為最佳的編碼模式。TSMD 內含有兩階層的決定過程︰第一個階段將根據先前巨區塊(Macro-Block)和前一影像(Video-Frame)所需要的編碼模式，預測現在巨區塊一些可能的編碼模式。第二個階段將同時利用，預先計算好的統計結果或者預先訓練好的半徑式基底函數類神經網路(BPN)的去重新評估決策。根據我們的實驗結果，與原先的編碼時間相比，超過50%的計算時間被降低，並在峰值雜訊比(PSNR)上只有些微的降低，此輕微的失真是不容易在視覺上被意識到。此研究的實驗部分，全部程式是使用H.264/AVC標準參考軟體，JM 9.2。
在最後的議題研究裡，我們提出一個以特徵點為基礎的數位影像浮水印演算法，這個演算法達到同時具有影像驗証跟版權保護的目標。首先，我們提出的浮水印崁入演算法是利用Hessian-Affine特徵偵測器萃取影像的特徵區域。然後版權浮水印將根據每個像素的區域內的特徵方向被嵌入這些特徵區域。而且，除了版權浮水印的嵌入區域外，我們再利用區塊式易碎型浮水印針對剩餘空間嵌入影像驗証浮水印。相同的，我們所提出的浮水印萃取的演算法將獨立地依循上述程序從浮水印影像去萃取版權浮水印和影像驗証資訊。為了驗證我們提出的演算法的穩定強健性，各種不同的攻擊被應用於本演算法所產生之浮水印影像。在這研究的實驗結果，顯示出我們所提出的演算法所產生的浮水印圖案可以抵抗大多數移動和幾何學攻擊。而且，改變或修改影像將可以反映在我們所隱藏的浮水印上。

Recently, high visual quality and efficient compression rate are the most important issues in multimedia compression system. Besides, image authentication and copyright protection become more and more essential in our digital life. Four important topics, wavelet image compression, halftone image processing, the speedup of video compression and image watermarking, in multimedia system are presented in this paper. In the first research, the hardware implementation of a modified efficient SPIHT coder is presented. Set Partitioning in Hierarchical Trees (SPIHT) is a highly efficient technique for compressing Discrete Wavelet Transform (DWT) decomposed images. Though its compression efficiency is a little less famous than Embedded Block Coding with Optimized Truncation (EBCOT) adopted by JPEG2000, SPIHT has a straight forward coding procedure and requires no tables. These make SPIHT the more appropriate algorithm for lower cost hardware implementation. The modifications include a simplification of coefficient scanning process, a 1-D addressing method instead of the original 2-D arrangement of wavelet coefficients, and a fixed memory allocation for the data lists instead of a dynamic allocation approach required in the original SPIHT. Although the distortion is slightly increased, it facilitates an extremely fast throughput and easier hardware implementation.
In the second research, a hybrid neural network based method for halftoning and inverse halftoning of digital images is presented. The halftone image is performed by Single-Layer Perceptron neural network (SLPNN), and its corresponding continuous-tone image is reconstructed by Radial-Basis Function neural network (RBFNN). The combined training procedure produces halftone images and the corresponding continuous tone images at the same time. The PSNR performance and visual image quality of these contone images achieved is comparable to the well-known inverse halftoning methods. Moreover, the halftone images obtained are also visually good.
In the third research, the speedup of H.264/AVC coders by examining the predicted modes in a code block is described. In a rate-distortion optimized H.264/AVC (H.264/RDO) coder, the best mode with the minimal Lagrange cost is selected after calculating the rate-distortion (R-D) cost which simultaneously considers the distortion and the required number of bits in all possible modes. H.264/RDO coders achieve a good balance between bit rate and image distortion, but lots of additional computing power is required. The proposed method, called two-staged mode decision (TSMD), only executes the modes which might be the best mode used in H.264/RDO coders with other modes disabled. TSMD employs a two-staged decision process: the first stage is to predict some probable encoding modes according to the information when one encodes the preceding macro-blocks and video frames. The second stage refines the decision with either the pre-computed look-up-table or the pre-constructed Back-Propagation Neural (BPN) network. According to our experiment results, over 50% of the computation time is reduced with a small loss in Peak Signal-to-Noise ratio (PSNR) and a slight bit-rate is incremented which are not easily sensed by human eyes. All programs are based on the H.264/AVC standard reference software, JM 9.2.
In the last research, a feature-based robust digital image watermarking algorithm is proposed to achieve the goal of image authentication and protection simultaneously. The Hessian-Affine feature detector is at first adopted to extract characteristic regions of an image in the proposed watermark embedding scheme. Then the copyright watermark is embedded into these characteristic regions according to the local orientation of each pixel. Moreover, the remainder regions are applied for image authentication by using block-wise fragile watermarking method. Similarly, the proposed watermark detection scheme follows the above procedure to extract the copyright watermark and the authentic information independently and blindly from watermarked images. Various attacks are also applied to the watermarked images in order to examine the robustness of our algorithm. The experimental results show that the proposed watermarking algorithm can resist most removal and geometric attacks. Besides, changes of an image will be reflected in our hidden watermarks.

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