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© 2011 Aifeng Ren

电子信息科学概论

任爱锋 电子工程学院E-mail: afren@ Office: 新科技楼A901 Phone: 88202830-607 Mobile: 133849195990

© EE141 电子信息科学概论

MTI

信息科学与电子工程专业英语

Unit 11Digital Image Processing

信息科学与电子工程专业英语

Part ITwo-Dimensional Digital Images

New Wordsparameter 参数 Intensity 强度

multi-spectral 多光谱的introductory 介绍性的，引导性的 amplitude 幅度 regions-of-interest 感兴趣区 rendition 表现，渲染

manipulate 处理，操作function函数 coordinate 坐标 motion blur 运动模糊 render 表现，渲染

real number 实数quantization 量化

integer 整数discrete 离散的

photon 光子magnetic resonance 磁共振

inherently 内在地，本质上phase 相位，相角3

New WordsMRI 磁共振成像 digitization 数字化 pixel 像素 sensor 传感器，感光器 round 四舍五入 outset 开头，最初 sampling 采样 intersection 交叉点 impinge 撞击，射到 monochromatic 单色的 convolution 卷积 perceptual 感官的

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1Images are two-dimensional signals representing spatial distribution of some physical parameters, typically light intensity, and more generally any form of energy. Motion pictures and multi-spectral remote sensing images, for example, are three or higher dimensional signals.

图像是表示一些物理参数空间分布的二维信号，典型的物理 参数是光强，而更普通的是能量的任一种形式。例如，运动 图像以及多光谱的遥感图像是三维或者是更高维的信号。

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1Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers.1

现代数字技术使得处理多维信号成为可能，所使用的系统可 从简单的数字电路到先进的并行计算机。

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1The goal of this manipulation can be divided into three categories: Image processing: image in image out Image analysis: image in measurements out Image understanding: image in high-level description out

这种处理的目的可以分为3类： 图像处理：输入图像 输出图像

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图像分析：输入图像 输出测量数据图像理解：输入图像 输出高层次的图像描述

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2We will focus on the fundamental concepts of image processing. Space does not permit us to make more than a few introductory remarks about image analysis and image understanding. Further, we will restrict ourselves to two-dimensional (2D) image processing although most of the concepts and techniques that are to be described can be extended easily to three or more dimensions.2

我们将介绍的重点集中在图像处理的基本概念上。篇幅所限， 我们只能对图像分析以及图像理解进行一些介绍性的说明。 另外我们将限于讨论二维图像处理，尽管将要描述

的大部分 概念和方法很容易扩展到三维或更高的维数。

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3We begin with certain basic definitions. An image defined in the ―real world‖ is considered to be a function of two real variables, for example, a(x, y) with a as the amplitude (e.g. brightness) of the image at the real coordinate position (x, y). An image may be considered to contain subimages sometimes referred to as regions-of-interest, ROIs, or simply regions. This concept reflects the fact that images frequently contain collections of objects each of which can be the basis for a region.

我们从一些基本定义开始。在“真实世界”中定义的一幅图 像可以看成是两个实变量的函数，例如：以a作为在实坐标位 置(x, y)处幅度(亮度)的图像a(x, y)。一幅图像可以看成是 包含许多子图像，这些子图有时称之为感兴趣区域，ROI, 或者仅仅是图像中的区域。这一概念表明图像通常包含许多 对象，每一个对象可以是一个区域的主要部分。9

3In a sophisticated image processing system it should be possible to apply specific image processing operations to selected regions. Thus one part of an image might be processed to suppress motion blur while another part might be processed to improve color rendition.3

在一个复杂的图像处理系统中，应该能对于选择的区域进行 特定的图像处理运算。于是图像的一部分可以进行抑制运动 模糊的处理，而另一部分可以作改进色彩渲染的处理。

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4The amplitudes of a given image will almost always be either real numbers or integer numbers. The latter is usually a result of a quantization process that converts a continuous range, say, between 0 and 100%, to a discrete number of levels.4

一幅给定图像的幅度几乎总是要么是实数，要么是整数。后 者通常是量化的结果，将一个连续的范围如0到100%转换为 离散的(灰度)级。

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4In certain image-forming processes, however, the signal may involve photon counting which implies that the amplitude would be inherently quantized. In other image forming procedures, such as magnetic resonance imaging, the direct physical measurement yields a complex number in the form of a real magnitude and a real phase. We will consider amplitudes as reals or integers unless otherwise indicated.

然而，在某些图像形成过程中，信号可能涉及到光子计数， 这意味着幅度本来是量化的。其它的图像形成过程，如磁共 振成像，直接的物理测量会产生一个复数，具有实的幅度和 实的相位。除非另有说明，我们认为幅度是实数或者是整数。

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5A digital image a[m, n] described in a 2D discrete space isderived from an analog image a(x, y) in a 2D continuous space

through a sampling process that is frequently referred to asdigitization.5

一幅二维离散空间中的数字图像a[m, n]是由二维连续空间中 的模

拟图像a(x, y)通过采样得到的。采样过程常称为数字化。

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5The mathematics of that sampling process will be described later. For now we will look at some basic definitions associated with the digital image. The effect of digitization is shown in Figure 11.1.

对采样过程的数学表示将在稍后介绍。现在，我们来看一些 和数字图像有关的基本定义。图11.1显示了数字化的效果。

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6The 2D continuous image a(x, y) is divided into N rows and M columns. The intersection of a row and a column is termed a pixel. The value assigned to the integer coordinates [m, n] with m = 0, 1, 2, ... , M 1 and n = 0, 1, 2, ... , N 1 is a[m, n].

2维连续图像a(x, y)被划分成N行M列。一行一列的交叉点被 叫做一个像素。整数坐标[m, n]被赋予的值是a[m, n],其中： m = 0, 1, 2, ... , M 1 ,n = 0, 1, 2, ... , N 1。

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6In fact, in most cases a(x, y), which we might consider to be the physical signal that impinges on the face of a 2D sensor, is actually a function of many variables including depth, color, and time.6 Unless otherwise stated, we will consider the case of 2D, monochromatic, static images in this text.

实际上，大多数情况下，我们认为是射到二维传感器表面的 物理信号a(x, y)实际上是许多变量的函数，包括深度、颜色、 时间。除非另作说明，本文我们考虑的是2维的，单色的静止 的图像情况。

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7The image shown in Figure 11.1 has been divided into N = 16 rows and M = 16 columns. The value assigned to every pixel is the average brightness in the pixel rounded to the nearest integer value.

图11.1的图像被划分成了N = 16 行以及M = 16列。赋予每个 像素的值是像素的平均亮度，其四舍五入到最近的整数。

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7The process of representing the amplitude of the 2D signal at a given coordinate as an integer value with L different gray levels is usually referred to as amplitude quantization or simply quantization.7

将二维信号在给定坐标位置的幅度表示成具有L个不同灰度 级的整数值的过程通常称为幅度量化，或简称量化。

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8Certain tools are central to the processing of digital images. These include mathematical tools such as convolution, Fourier analysis, and statistical descriptions, and manipulative tools such as chain codes and run codes. Here we present these tools without any specific motivation. The motivation will follow in later sections.

在数字图像处理中，某些工具是非常重要的。这些包括数学 工具，如：卷积、傅立叶分析以及统计描述，和处理工具， 如：链式码与游程码。在这里我们介绍这些工具没有任何特 别的动机，在后面的章节中我们会对此予以介绍。

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9Many image processing applications are intended to produce images that are to be viewed by human observers as opposed to, say, automated industrial inspection. It

is therefore important to understand the characteristics and limitations of the human visual system ― to understand the ―receiver‖ of the 2D signals.

许多图像处理应用是要产生被人观察的图像，而不是比方说 为了自动的工业检验。因此，了解人类视觉系统的特征和限 制是很重要的，即要了解二维信号的“接收器”。

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