我們提出了一個針對影像畫面間壓縮的無損演算法，其中包含了字典編碼方法、赫夫曼演算法以及三個方式以達到更高的壓縮率。我們藉由分析當前像素和其週遭像素間差值的分佈，發現了當此差值的絕對值越低其比率越高，根據前述差值分佈數據，我們可以計算出當使用不同數量編碼時候的資料壓縮率，並且發現了使用越多數量的編碼壓縮比率會越高但是會趨於平緩。考慮到記憶體的使用，在此論文中，我們選出了一個適合的編碼數量並且以赫夫曼演算法的方式來產生編碼，畫面間的像素能夠使用相對應的編碼應用合稱為兩階段驗證方式的字典編碼法以及字首最長匹配法的方式壓縮，接下來我們會在APBT中選出每組像素在字首最長匹配法中最佳的截斷度，我們會再將編碼使用首碼壓縮法的方式壓縮。藉由指定並且使用數量更多的編碼，相對於之前提出的相似演算法，可以達到平均約0.5%的縮率的改善，並且相較於使用最大的字典編碼，壓縮率的差距只0.96%而已。

We propose a lossless video frame compression algorithm employing a dictionary coding method, the Huffman coding method and three schemes to achieve high compression ratio. We observe the smaller the absolute value of the differentials between the current pixel and its neighbors the higher the probability is by analyzing the distribution of this differentials. According to this distribution, we compute the data reduction ratio (DRR) for cases using different numbers of code words and find the more code words used the higher the DRR which approached a plateau. Considering memory usage, we choose a suitable number of code words for Huffman encoding. We employ a two-staged classification (TC) scheme consisting of the dictionary coding method and a longest prefix match (LPM) method. The LPM method we choose for each pixel group a best truncation length (BTL) using an adaptive prefix bit truncation (APBT) scheme. We further compress the code words by a head code compression (HCC) scheme. Due to large numbers of code words used, we can achieve about 0.5% more bit rate reduction compared to previous proposed algorithm and only 0.96% bit rate reduction less than using the maximum dictionary size.

Abstract ............................................................................................................................. iii
Contents ............................................................................................................................. iv
List of Figures .................................................................................................................... iv
List of Tables ..................................................................................................................... vi
Chapter 1 Introduction ..................................................................................................... 1
Chapter 2 Previous Work ................................................................................................. 4
2.1 Block-Based Lossless Compression Algorithm ................................................... 4
2.2 Line-Based Lossless Compression Algorithm ..................................................... 5
2.3 Summary of Previous Work ................................................................................. 6
Chapter 3 Analysis of Differentials Between Neighboring Pixels ................................. 7
3.1 Fixed Location Neighbor ..................................................................................... 7
3.2 Median of a Group of Neighbors ....................................................................... 12
3.3 Summary of Differentials Between Neighboring Pixels ................................... 14
Chapter 4 Proposed Algorithm ....................................................................................... 16
4.1 Overview ............................................................................................................ 16
4.2 Reference Neighbor Selection ........................................................................... 18
4.3 Two-Stage Classification Scheme ..................................................................... 20
4.4 Adaptive Prefix Bit Truncation Scheme ............................................................ 23
4.5 Code Word Assignment ..................................................................................... 24
4.6 Head Code Compression .................................................................................... 27
4.7 An Illustrative Example ..................................................................................... 29
Chapter 5 Experimental Results ..................................................................................... 31
5.1 Environment ....................................................................................................... 31
5.2 Data Reduction Ratio Result .............................................................................. 33
Chapter 6 Conclusions and Future Work ..................................................................... 39
References ......................................................................................................................... 41

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