基于矢量量化的高效BTC图像编码算法

作为一种有损图像编码技术，块截短编码算法（BTC）的计算量较少，速度快，有较好的信道容错力，重建图像质量较高。然而，标准BTC算法的主要缺点是其压缩比特率比其他基于块图像编码的算法（如变换编码和矢量量化）高。为了降低比特率，提出了几种有效的BTC算法，还提出了一种简单的查表算法对每块的BTC量化数据编码，另外还引入了矢量量化技术以减少对位平面编码的比特数。为了减少由改进算法引入的额外失真，在每种提出的算法中，采用最优阈值而不用平均值作为量化阈值。

An Efficient VQ-based BTC Algorithm in Image Coding

Block truncation coding (BTC) is an efficient and fast lossy image coding technique. However, the main shortcoming of the standard BTC algorithm is a relatively high bit rate of 2.0 bits per pixel compared to other block-based image coding schemes such as transform coding and vector quantization. In order to reduce the bit rate, four efficient BTC algorithms are presented to reduce the number of bits required to code the two quantization data and the bit plane, which are created by BTC for each image block. On the one hand, simple look-up-table methods are presented to code the BTC quantized data of a block. On the other hand, vector quantization technique is introduced to reduce the number of bits used to code the bit plane. In order to reduce the extra distortion induced by the proposed algorithms, we use the optimal threshold instead of the mean value as the quantization threshold in each proposed algorithm. Experimental results prove the effectiveness of the proposed algorithms.