Image Recalling for Discrimination by Wavelet Based Neural Networks

机译：基于小波神经网络的图像调用识别

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In this paper, a novel wavelet based neural system for color image recalling and discrimination is proposed. First, color images are memorized in learning process based on human visual perceptive model. Using the multi-resolution wavelet decomposition, the approximation components are memorized to reduce the computational load. Next, in the recalling process, noisy uncertain image is used as an input to the wavelet based neural system. By recurrent processes, the approximation component of the corresponding original image is recalled. The detail component is obtained to execute the de-noising process by threshold processing. In the simulations, several uncertain color texture images such as partially buried, blurred and noisy images are used. It is shown that the incomplete color texture image is effectively restored and discriminated by the proposed neural system. The performance of discrimination is evaluated in terms of the PSNR and the perceptual viewpoint. The robustness for incompleteness is also examined.

机译：本文提出了一种基于小波神经网络的彩色图像召回和识别新系统。首先，在基于人类视觉感知模型的学习过程中存储彩色图像。使用多分辨率小波分解，可以存储近似分量以减少计算量。接下来，在召回过程中，将嘈杂的不确定图像用作基于小波的神经系统的输入。通过循环过程，可以调用相应原始图像的近似分量。通过阈值处理获得细节分量以执行去噪处理。在仿真中，使用了一些不确定的颜色纹理图像，例如部分掩盖的，模糊的和有噪点的图像。结果表明，所提出的神经系统可以有效地恢复和识别不完整的彩色纹理图像。根据PSNR和感知角度评估判别性能。还检查了不完整性的鲁棒性。

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《International Conference on Cybernetics and Information Technologies, Systems and Applications(CITSA2004) and 10th International Conference on Information Systems Analysis and Synthesis(ISAS2004) vol.3》|2004年|P.164-167|共4页
会议地点 OrlandoFL(US)
作者
Yutaka YAGYU; Shigeo WADA;
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作者单位

Graduate School of Engineering, Tokyo Denki University, 2-2 Kanda-Nishiki-cho, Chiyoda-ku, Tokyo 101-8457 Japan;

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会议组织
原文格式 PDF
正文语种 eng
中图分类通信;
关键词
wavelets; recurrent neural networks; image discrimination; de-noising; human visual system;

机译：小波;递归神经网络;图像识别;去噪;人类视觉系统;

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Image Recalling for Discrimination by Wavelet Based Neural Networks

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