基于BWT和FVQ的極低比特率圖像編碼算法
BWT AND FVQ BASED VERY LOW BIT RATE IMAGE CODING ALGORITHM
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摘要: 該文提出了一種基于雙正交小波變換(BWT)和模糊矢量量化(FVQ)的極低比特率圖像編碼算法。該算法通過(guò)構(gòu)造符合圖像小波變換系數(shù)特征的跨頻帶矢量，充分利用了不同頻帶小波系數(shù)之間的相關(guān)性，有效地提高了圖像的編碼效率和重構(gòu)質(zhì)量。該算法采用非線性插補(bǔ)矢量量化(NLIVQ)的思想，從大維數(shù)矢量中提取小維數(shù)的特征矢量，并提出了一種新的模糊矢量量化方法一漸進(jìn)構(gòu)造模糊聚類(PCFC)算法用于特征矢量的量化，從而大大提高了矢量量化的速度和碼書質(zhì)量。實(shí)驗(yàn)結(jié)果證明，該算法在比特率為0．172bpp的條件下仍能獲得PSNR＞30dB的高質(zhì)量重構(gòu)圖像。
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關(guān)鍵詞:
- 雙正交小波變換;矢量量化;模糊聚類;漸進(jìn)構(gòu)造;非線性插補(bǔ)
Abstract: A biorthogonal wavelet transform (BWT) and fuzzy vector quantization (FVQ)based very low bit rate image coding algorithm is proposed.The correlation of the wavelet coefficients in different frequency bands is fully exploited through constructing the band-cross vector,so the high coding efficiency and reconstructed image quality are obtained simulta-neously.In addition,a hybrid vector quantization (VQ) scheme is presented to improve the performance of VQ,which combines the non-linear interpolated vector quantization (NLIVQ)technique with a novel progressive constructive fuzzy clustering algorithm.Simulation results demonstrate that the reconstruction quality is higher than 30dB at a very low bit rate of 0.172bpp. -
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