期刊
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
卷 92, 期 4, 页码 435-444出版社
SPRINGER
DOI: 10.1007/s11265-019-01477-2
关键词
Image mosaic; Image feature extraction; Convolutional neural network; Neural network attack
Since traditional image feature extraction methods rely on features such as corner points, a new method based on semantic feature extraction is proposed inspiring by convolution neural attack. The semantic features of each pixel in an image are computed and quantified by neural network to represent the contribution of each pixel to the image semantics. According to the quantization results, the semantic contribution values of each pixel are sorted, and the semantic feature points are selected from high to low and the image mosaic is completed. Experimental results show that this method can effectively extract image features and complete image mosaic.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据