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基于小波投影和离散哈希的图像检索
引用本文:荣梦君,刘惊雷.基于小波投影和离散哈希的图像检索[J].模式识别与人工智能,2020,33(11):1023-1032.
作者姓名:荣梦君  刘惊雷
作者单位:1.烟台大学 计算机与控制工程学院 烟台 264005
基金项目:国家自然科学基金;国家自然科学基金;国家自然科学基金;国家自然科学基金
摘    要:现有的哈希方法难以快速实现原始特征空间的近似映射.针对此问题,文中提出基于小波投影的哈希方法.基于Haar小波变换构造投影矩阵,使用迭代算法优化投影矩阵和离散优化二进制码,重构量化误差.利用投影矩阵将图像的原始特征向量快速投影至低维空间,并进行二进制嵌入,完成图像的哈希编码.在图像数据集上的实验表明,文中方法可有效提升编码效率.

关 键 词:Haar小波变换  二进制嵌入  维度约简  随机投影  
收稿时间:2020-08-10

Image Retrieval Based on Wavelet Projection and Discrete Hashing
RONG Mengjun,LIU Jinglei.Image Retrieval Based on Wavelet Projection and Discrete Hashing[J].Pattern Recognition and Artificial Intelligence,2020,33(11):1023-1032.
Authors:RONG Mengjun  LIU Jinglei
Affiliation:1. School of Computer and Control Engineering,Yantai University,Yantai 264005
Abstract:Existing hashing methods can hardly realize the approximate mapping of the original feature space quickly.Therefore,a hashing method based on wavelet projection is proposed.Firstly,the projection matrix is constructed based on Haar wavelet transform.The projection matrix is optimized iteratively and binary codes are optimized by discrete method to control the quantization error.Then,the projection matrix is utilized to project the original feature vector of the image into the low-dimensional space quickly and binary codes are obtained by binary embedding.Experimental results on image datasets demonstrate that the proposed method improves encoding efficiency effectively.
Keywords:Haar Wavelet Transform  Binary Embedding  Dimensionality Reduction  Randomized Projection  
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