Source: http://www.cnblogs.com/GarfieldEr007/p/5015474.html
From: ittbank
Digital image processing refers to the process of converting image signals into digital signals and processing them with a computer. Image processing first appeared in the 1950s, when electronic computers had developed to a certain level, and people began to use computers to process graphics and image information. Digital image processing as a discipline was formed around the early 1960s. The purpose of early image processing is to improve the quality of the image. It takes people as objects and aims to improve people's visual effects. In image processing, low-quality images are input, and images with improved quality are output. Commonly used image processing methods include image enhancement, restoration, encoding, and compression.
Common methods of digital image processing:
1) Image transformation
Since the image array is large, processing it directly in the spatial domain involves a large amount of computation. Therefore, various image transformation methods, such as Fourier transform, Walsh transform, discrete cosine transform and other indirect processing techniques, are often used to convert the processing of the spatial domain into the processing of the transform domain, which can not only reduce the amount of calculation, but also obtain more efficient processing (such as Fourier transform can be digitally filtered in the frequency domain). The emerging wavelet transform has good localization properties in both time and frequency domains, and it also has extensive and effective applications in image processing.
2) Image coding and compression
Image coding and compression techniques reduce the amount of data (ie, the number of bits) that describe an image, in order to save image transmission, processing time and reduce the amount of memory occupied. Compression can be achieved without distortion or with distortion allowed. Coding is the most important method in compression technology, and it is the earliest and more mature technology in image processing technology.
3) Image enhancement and restoration
The purpose of image enhancement and restoration is to improve the quality of the image, such as removing noise and improving the clarity of the image. Image enhancement highlights the parts of interest in the image regardless of the cause of image degradation. If the high-frequency components of the image are enhanced, the outlines of objects in the image can be clear and the details are obvious; if the low-frequency components are enhanced, the influence of noise in the image can be reduced. Image restoration requires a certain understanding of the reasons for image degradation. Generally speaking, a "degradation model" should be established according to the degradation process, and then a certain filtering method should be used to restore or reconstruct the original image.
4) Image segmentation
图像分割是数字图像处理中的关键技术之一。图像分割是将图像中有意义的特征部分提取出来，其有意义的特征有图像中的边缘、区域等，这是进一步进行图像识别、分析和理解的基础。虽然目前已研究出不少边缘提取、区域分割的方法，但还没有一种普遍适用于各种图像的有效方法。因此，对图像分割的研究还在不断深入之中，是目前图像处理中研究的热点之一。
5 ）图像描述
图像描述是图像识别和理解的必要前提。作为最简单的二值图像可采用其几何特性描述物体的特性，一般图像的描述方法采用二维形状描述，它有边界描述和区域描述两类方法。对于特殊的纹理图像可采用二维纹理特征描述。随着图像处理研究的深入发展，已经开始进行三维物体描述的研究，提出了体积描述、表面描述、广义圆柱体描述等方法。
6 ）图像分类（识别）
图像分类（识别）属于模式识别的范畴，其主要内容是图像经过某些预处理（增强、复原、压缩）后，进行图像分割和特征提取，从而进行判决分类。图像分类常采用经典的模式识别方法，有统计模式分类和句法（结构）模式分类，近年来新发展起来的模糊模式识别和人工神经网络模式分类在图像识别中也越来越受到重视。
图像的基本属性
亮度：也称为灰度，它是颜色的明暗变化，常用 0 ％～ 100 ％ ( 由黑到白 ) 表示。以下三幅图是不同亮度对比。
亮度对图像色彩的影响
对比度：是画面黑与白的比值，也就是从黑到白的渐变层次。比值越大，从黑到白的渐变层次就越多，从而色彩表现越丰富。
对比度对图像色彩表现的影响
直方图：表示图像中具有每种灰度级的象素的个数，反映图像中每种灰度出现的频率。图像在计算机中的存储形式，就像是有很多点组成一个矩阵，这些点按照行列整齐排列，每个点上的值就是图像的灰度值，直方图就是每种灰度在这个点矩阵中出现的次数。我们可以具体看一下下面两个不同图形的灰度直方图：
直方图均衡化
通过灰度变换将一幅图像转换为另一幅具有均衡直方图的图像，即在一定灰度范围内具有相同的象素点数的图像的过程。下面是直方图均衡化前后的图形变化以及直方图变化：
图像的加减运算
两幅图像的加减运算：对图像进行加减运算，就是将图像对应的存储矩形点列上的灰度值进行加减运算。图像相加可以将一幅图像的内容加到另一幅图像上，可以实现二次曝光，也可一对同一个场景的多幅图像求平均值，这样可以降低噪声。图像相减可以用于运动检测或去除图像中不需要的加性图案。
图像的加法示例：图中运算为： (a)+(b)=(c)
图像的减法运算示例：图中运算为 (a)-(b)=(c)
图像的噪声
图像的噪声：就像对于听觉而言，在打电话时对方说话我们有时候会听到很嘈杂的噪声，以至于听不清楚对方在说什么。同样的，对于图像，原本我们可以很清晰的看到一幅图像，但是有时候图像上会有一些我们不需要的图案，使我们无法很清楚的看清一幅图，这就是图像的噪声。
常用的图像去噪声方法
常用的去噪方法：主要是采用滤波器对带噪声图像进行滤波处理。
数字图像处理技术的应用
随着计算机技术的发展，图像处理技术已经深入到我们生活中的方方面面，其中，在娱乐休闲上的应用已经深入人心。图像处理技术在娱乐中的应用主要包括：电影特效制作、电脑电子游戏、数码相机、视频播放、数字电视等
电影特效制作：自从 20 世纪 60 年代以来，随着电影中逐渐运用了计算机技术，一个全新的电影世界展现在人们面前，这也是一次电影的革命。越来越多的计算机制作的图像被运用到了电影作品的制作中。其视觉效果的魅力有时已经大大超过了电影故事的本身。如今，我们已经很难发现在一部电影中没有任何的计算机数码元素。
电脑电子游戏：电脑电子游戏的画面，是近年来电子游戏发展最快的部分之一。从 1996 年到现在，游戏画面的进步简直可以用突飞猛进来形容，随着图像处理技术的发展，众多在几年前无法想象的画面在今天已经成为了平平常常的东西。
Digital camera: The so-called digital camera is a special camera that can take pictures and convert the captured scene into a digital format through internal processing. Unlike ordinary cameras, digital cameras do not use film, but use fixed or detachable semiconductor memory to store captured images. Digital cameras can be connected directly to a computer, TV, or printer. Under certain conditions, the digital camera can also be directly connected to a mobile phone or a handheld PC. Since the images are processed in-house, the user can immediately check that the images are correct and can be printed or emailed right away.
Video playback and digital TV: VCDs, DVD players and digital TVs in home theaters use a lot of image processing technologies such as video coding and decoding, and the development of video coding and decoding and other image processing technologies has also promoted video playback and digital TV. Like high-definition, high-quality development.
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