Contourlet变换在图像压缩中的应用研究

目前基于小波变换的图像压缩方案比较普遍。而二维小波只是一维小波的张量积，基
函数的支撑区域由区间扩展为正方形，只有有限个方向。Contourlet 变换是一种图像的多尺度几何分析工具，能够稀疏表示图像，非线性逼近能力很强，它的基函数则具有方向性，各向异性。本文在分析了Contourlet 变换的基础上，对变换后的重要系数和其位置进行了编码。对标准图像barbara 进行测试，实验结果表明：基于Contourlet 变换的方案和基于小波变换的方案相比，峰值信噪比平均提高约0.5dB，且采用Contourlet 变换能够较好地保留图像中的纹理，图像的主观视觉质量较好。
关键词：图像压缩 Contourlet 小波变换
Abstract: The image compression method based on wavelet is used more widely nowadays. However, two dimensional wavelet is the tensor product of the one dimensional wavelet whose support region of basis function is extended from interval to square. It has only a few directions. Contourlet is a new image multiscale geometric analysis tool, which could represent image sparsely and has strong capability of nonlinear approximation. The basis function of contourlet is multi-directional and anisotropic. This paper analyzes the contourlet transform and coding the significant coefficients and its position. The standard test image Barbara is tested and experimental result shows that comparison with scheme based on wavelet the PSNR of the scheme using contourlet increases about 0.5dB and using contourlet could retains the texture of the image and get superior subject vision quality.
Key words: Image compression; Contourlet; Wavelet transform