摘要
针对图像小波系数的能量聚集特性,提出一种基于截断重排的小波图像无损压缩算法。该算法在离散小波变换的基础上,对图像低频子带的小波系数先后按照大津法和希尔伯特曲线进行分类和重排,对图像各高频子带的小波系数分别根据信息熵代价函数进行自适应的奇异值截断变换,然后对截断重排后的所有小波系数进行熵编码,以实现图像无损压缩。实验结果表明,该算法实现简单,有效地降低了图像的编码比特率,提升了图像无损压缩的压缩比。
According to the energy aggregation properties of image wavelet coefficients, a new wave- let image lossless compression algorithm based on rearrangement and truncation is proposed. On the basis of discrete wavelet transform, the algorithm successively classifies and rearranges the low frequency sub-- band coefficients in line with Otsu method and Hilbert curve, while, respectively makes adaptive trun- cated singular value transform on all the high frequency sub-bands in light of information entropy cost function, followed by entropy encoding for lossless compression. Experimental results show the proposed algorithm effectively reduces encoding tio of image lossless compression. bit rate with simple implementation, improving the compression ra-.
出处
《宇航计测技术》
CSCD
2013年第3期39-43,共5页
Journal of Astronautic Metrology and Measurement
关键词
图像无损压缩
小波变换
分类重排
奇异值截断变换
Image lossless compression Wavelet transform Classified rearrangement Singu--lar value truncation transform
