一種改進(jìn)的矢量量化碼字搜索算法
An improved codeword searching algorithm for vector quantization
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摘要: 該文利用圖像矢量的平均值和方差,結(jié)合了最近鄰域搜索算法,構(gòu)造了一種新的快速矢量量化編碼算法。將一個(gè)輸入矢量分為兩個(gè)子矢量,分別計(jì)算原始矢量、兩個(gè)子矢量的和以及方差值,利用在這些數(shù)值基礎(chǔ)上建立的一組三角不等式來排除不可能的碼字。仿真結(jié)果表明新算法在所需時(shí)間和計(jì)算復(fù)雜度方面優(yōu)于改進(jìn)的EENNS算法,為矢量量化算法的研究提供了一種新的思路。
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關(guān)鍵詞:
- 矢量量化; 最近鄰域搜索; EENNS算法
Abstract: In this paper, an improved codeword searching algorithm is proposed on the basis of nearest-neighbor search algorithm. The new algorithm considers the sums and variances of image vectors. A vector is separated into two subvectors: the first half of the coordinates and the second half of the coordinates. Calculate the sums and variances of the vector and its two subvectors. Apply the result to a set of inequalities to eliminate the impossible codeword candidates. The simulation results show that the proposed algorithm is faster than the improved EENNS algorithm, and it also has the advantage in decreasing the computing complexity. -
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