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Research On Image Compression Technology Based On Bp Neural Network

机译:基于Bp神经网络的图像压缩技术研究。

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The traditional image compression technique uses the redundancy of the image data to compress the image without lossless coding by the corresponding coding techniques. Different compression coding techniques are redundant for different image data. Under the background of many new applications, the traditional image compression technology can no longer meet the requirement of further improving the quality of compressed images. In recent years, with the continuous development of artificial neural network technology, Some good properties of neural network, such as nonlinear, fault-tolerant, self-organizing and adaptive, has been widely applied in image processing technology, which greatly simplifies the complexity of image processing. This paper mainly introduces the basic principles of BP neural network, studies the application of neural network in image compression, carries out simulation experiments through MATLAB, and analyzes the feasibility and advantages of BP neural network applied to image compression.
机译:传统的图像压缩技术使用图像数据的冗余来压缩图像,而无需通过相应的编码技术进行无损编码。对于不同的图像数据,不同的压缩编码技术是多余的。在许多新应用的背景下,传统的图像压缩技术已不能满足进一步提高压缩图像质量的要求。近年来,随着人工神经网络技术的不断发展,非线性,容错,自组织和自适应等神经网络的一些优良特性已广泛应用于图像处理技术中,大大简化了神经网络的复杂度。图像处理。本文主要介绍了BP神经网络的基本原理,研究了神经网络在图像压缩中的应用,通过MATLAB进行了仿真实验,分析了BP神经网络在图像压缩中的可行性和优势。

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