臺灣博碩士論文加值系統

向量量化是一種關於低位元比率影像編的有效技術。然而，向量量化影像
編碼的初期研究揭示了一些難處，主要是在影像邊緣部分和高計算複雜性
o 雖然已經有些方法針對影像邊緣編碼，如區塊截斷編碼與向量量化或分
類式向量量化，但是其壓縮比還不能令人滿意。在另一方面，離散餘弦轉
換與向量量化應用於影像壓縮，是可以得到高壓縮比，但是其影像邊緣的
效果較差。我們提出一種影像壓縮演算法，利用DCT/VQ及BTC/VQ以達到高
畫質及高壓縮比。實行此演算法可得到壓縮率0.34..0.46(位元/影像點)o

Vector quantization (VQ) is a powerful technique for low bit
rate image coding. However, initial studies of image coding
with VQ have revealed difficulities, most notably edge
degradation and high computational complexity. Although there
are many algorithms developed to keep the image from edge
degradation, such as block truncation coding with VQ (BTC/VQ)
or classified vector quantization, the compression ratio could
not be satisfactory. On the other hand, discrete cosine
transform with VQ (DCT/VQ) has beeb applied to image
compression, it gains high compression ratio but the edge
degradation problem still exists. We present an image
compression algorithm that takes the advantage of the DCT/VQ
and BTC/VQ to achieve a high quality and low-bit rate
compression of images. High quality image can be achieved at
rates 0.34 .. 0.46 (bits/pixel).