基于小波散射网络下的图像检索

小波散射卷积神经网络由于其优越的性能而被迅速、广泛地运用到图像、音频等领域.本文利用这种新型的网络结构提取图像的特征，结合相似度度量方法，实现该特征提取在图像检索方面的应用.此外，将小波散射网络得到的特征系数，以其均值和方差作为新的特征，实现大规模图像检索的降维.最后，利用实验算法对比验证了上述降维方法的可行性和优越性.

Image Retrieval Based on Wavelet Scattering Network

Due to superior performance of the wavelet scattering network, it is rapidly and widely used in the fields of image and audio. This new type of network structure is used to extract the features of the image and combines similarity measurement methods to achieve the application of this feature extraction in image retrieval. In addition, the eigenvalues obtained by the wavelet scattering network are taken as its new features, taking the mean value and the variance as the new features, so as to realize the dimensionality reduction of large-scale image retrieval. Finally, the experimental algorithm is used to verify the feasibility and superiority of the above dimensionality reduction method.