提出了一种利用小波变换对图象进行多尺度检索的方法。这种方法首先对图象进行多尺度小波分解，然后求出分解后尺度系数矩阵的各阶顺序子矩阵的F－范数，用F－范数定义图象的特征向量和相似度，再利用这种相似度进行图象检索。为了提高运算速度，使用的只是一维整数小波变换。整数小波变换的优点是：只需进行位内运算，输入和输出是整数，存储量小，适合图象处理；用F－范数形成的特征向量维数低，检索效率高。通过对200幅左右花卉和山水彩色图象数据库进行实验表明，该算法能够较好地描述图象的尺度和颜色分布信息，检索效果较好。

This paper presents a method of image multi scale retrieval. That is by means of wavelet transform, which firstly decomposes an image in multi scale, which yields a scalable coefficient matrix; secondly determines the F norms of all the ordinal sub matrixes of the scalable coefficient matrix; and then defines the features and similarities of images by the F norms; finally uses these similarities index images. But in order to speed up the computation, this paper only deals with the Integer to Integer Wavelet Transform, the main advantages of which are: all the calculations can be done in place; the input and output values are all integers; and only a small memory is required. Additionally, the feature vector based on F norm is low in dimension, and efficient in retrieval. The experimental results of a database of about 200 color images of flower and mount show this algorithm can well capture the scale and color information of images and can lead to better results.