信息与计算科学毕业论文之欧阳史创编

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欧阳史创编 2021..02.10

摘要

时间：2021.02.10 创作：欧阳史信息论是人们在长期通信实践活动中，由通信技术与概率论、随机过程、数理统计等学科相结合而逐步发展起来的一门新兴交叉学科。而熵是信息论中事件出现概率的不确定性的量度，能有效反映事件包含的信息。随着科学技术，特别是信息技术的迅猛发展，信息理论在通信领域中发挥了越来越重要的作用，由于信息理论解决问题的思路和方法独特、新颖和有效，信息论已渗透到其他科学领域。随着计算机技术和数学理论的不断发展，人工智能、神经网络、遗传算法、模糊理论的不断完善，信息理论的应用越来越广泛。在图像处理研究中，信息熵也越来越受到关注。为了寻找快速有效的图像处理方法，信息理论越来越多地渗透到图像处理技术中。本文通过进一步探讨概论率中熵的概念，分析其在图像处理中的应用，通过概念的分析理解，详细讨论其在图像处理的各个方面：如图像分割、图像配准、人脸识别，特征检测等的应用。

本文介绍了信息熵在图像处理中的应用，总结了一些基于熵的基本概念，互信息的定义。并给出了信息熵在图像处理特别是图像分割和图像配准中的应用，最后实现了信息熵在图像配准中的方法。

关键词：信息熵，互信息，图像分割，图像配准

Abstract

Information theory is a new interdisciplinary subject developed in people long-term communication practice, combining with communication technology, theory of probability, stochastic processes, and mathematical statistics. Entropy is a measure of the uncertainty the probability of the occurrence of the event in the information theory, it can effectively reflect the

欧阳史创编 2021..02.10

information event contains. With the development of science and technology, especially the rapid development of information technology, information theory has played a more and more important role in the communication field, because the ideas and methods to solve the problem of information theory is unique, novel and effective, information theory has penetrated into other areas of science. With the development of computer technology and mathematical theory, continuous improvement of artificial intelligence, neural network, genetic algorithm, fuzzy theory, there are more and more extensive applications of information theory. In the research of image processing, the information entropy has attracted more and more attention. In order to find the fast and effectiveimage processing method, information theory is used more and more frequently in the image processing technology. In this paper, through the further discussion on concept of entropy, analyzes its application in image processing, such as image segmentation, image registration, face recognition, feature detection etc.

This paper introduces the application of information entropy in image processing, summarizes some basic concepts based on the definition of entropy, mutual information. And the information entropy of image processing especially for image segmentation and image registration. Finally realize the information entropy in image registration.

Keywords：Information entropy, Mutual information, Image segmentation,

Image registration

欧阳史创编 2021..02.10

摘要...........1 ABSTRACT2 目录3 1 引言5

1.1 信息熵的概念5

1.2信息熵的基本性质及证明6 1.2.1单峰性6 1.2.2对称性7 1.2.3渐化性7 1.2.4展开性7 1.2.5确定性8

2 基于熵的互信息理论9 2.1互信息的概述9 2.2互信息的定义9

2.3熵与互信息的关系9

3信息熵在图像分割中的应用11 3.1图像分割的基本概念11

3.1.1图像分割的研究现状11 3.1.2图像分割的方法11

3.2基于改进粒子群优化的模糊熵煤尘图像分割12 3.2.1基本粒子群算法12

3.2.2改进粒子群优化算法13 3.2.3Morlet变异13