从小波分析的理论及研究现状出发,阐述了小波分析在图像压缩中的应用,并通过实验说明小波分析在图像处理中的作用。实验以matlab7.0作为平台,使用wavedec2和appcoef2函数进行二维小波分解和获取小波分解的近似分量,并且使用detcoef2函数来获取两层二维小波分解的细节分量,最后使用wrcoef2函数对各层的分量进行重构。实验表明,利用小波分析对图像进行压缩可以得到非常好的压缩效果。
From the theory of wavelet analysis and the research situation, the paper makes a brief description of image compression based on wavelet analysis and the important role of waveless analysis in the experimental image processing. With matlab7.0 as a platform in the experiment, wavedec2 and appcoef2 functions are used to realize two-dimensional wavelet decomposition and acquire the approximate weight of wavelet decomposition, while in addition, detcoef2 function is used to acquire the details of the two-dimensional wavelet decomposition. Finally wrcoef2 function is used to reconstruct the weight of each layer. The experimental result indicates that the application of wavelet analysis in image compression could achieve very good compression result.