基于提升小波的图像检索算法

摘要

提升小波具有高效性和多分辨率等优点,本文提出了基于提升小波的图像检索算法.该算法首先对图像进行提升小波变换,得到每层的低频子图像和高频子图像；然后分别提取低频子图像的形状特征和高频子图像的纹理特征；最后通过计算特征向量之间的欧式距离,检索出相似的图像.实验结果表明,此算法的检索效率高于其他算法,具有一定的优越性和通用性.%In this paper, an image retrieval algorithm is proposed based on lifting wavelet, for it has many advantages such as high efficiency and resolution. Firstly, through lifting wavelet transform of the image, we can get each layer of the low-frequency sub-image and high-frequency sub-images. Then, shape feature of low-frequency sub-image and texture feature of high-frequency sub-images can be extracted. Finally, the Euclidean distance is calculated between the feature vectors and retrieved similar images. Experimental results show that the retrieval efficiency of this algorithm is better than other algorithms. It has advantages and versatility.