江苏大学（机器视觉）大作业报告题目：图像增强专业：测控技术与仪器班级：1202学号：学生姓名：完成时间：2015年6月说明大作业的要求和内容：一、内容要求对机器视觉中所用的某一技术进行综述，必须用英文书写。

二、格式要求参照报告样例格式。

三、评分依据书写内容是否详尽到位50%语言方面是否通顺，有无错误20%对应PPT制作的好坏10%英文演讲的好坏20%四、其他说明大作业务必独立完成，一经发现雷同作“0”分处理。

教师小结：成绩：教师签名：目录1 The introduction (5)2 The research status at home and abroad (7)3 Key technology (method) is introduced (11)4 conclusion (13)参考文献 (15)图像增强技术（江苏大学机械工程学院仪器科学与工程系，江苏，镇江，212013）摘要：图像增强技术是增强图像中的有用信息，它可以是一个失真的过程，其目的是要改善图像的视觉效果，针对给定图像的应用场合，有目的地强调图像的整体或局部特性，将原来不清晰的图像变得清晰或强调某些感兴趣的特征，扩大图像中不同物体特征之间的差别，抑制不感兴趣的特征，使之改善图像质量、丰富信息量，加强图像判读和识别效果，满足某些特殊分析的需要。

本文就图像增强技术的分类、基本方法以及国内外发展状况做一些简单的介绍。

关键词：图像增强；视觉效果；图像质量Image enhancementAbstract: Image enhanced technology,a process of distortion, is the useful information to enhanced image,whose purposes is to improved the Visual effect of the image.According to the given application occasions of the imagine, to stressed the overall or local characteristics of the imagine. It will turn the originally blur image into clear or stressed some features of intrest, expanded the gap in different objects features of the image, inhibit the features that are not interest, to improved the image quality, and rich its information, strengthened image’s effect of interpretation and recognition, to meet some special needs of analysis. This article simply introduced the categories of the image enhancement technologies, the basic methods and the developments at home and abroad.Keywords: Image enhancement; Visual effects; Image quality1 The introductionIn general, the image transmission and conversion, such as imaging, replication, scanning, transmission and display, etc., often cause the image quality decline, that is, image distortion. In photography due to the light illumination is insufficient or excessive, will make the image is too dark or too bright; optical system distortion, relative motion, air flow will make the image fuzzy, transmission will introduce various types of noise. In short, the image of the image in the visual effect and identification of the convenience and other aspects may exist many problems, such problems might as well collectively referred to as quality issues. Image enhancement is based on the specific need to highlight the important information in the image, while weakening or removing the need for information. Images obtained from different ways, through appropriate enhancement, the originally smudgy even unable to distinguish the original image into clear contains a lot of useful information can use the image and effectively remove image noise, enhance image edges or other interested regional and thus easier to image in the target detection and measurement. Whether the image is kept undisturbed or not is irrelevant, and will not be conscious of the image's authenticity because of the ideal form of the image.. The purpose of the image enhancement is to enhance the visual effect of the image, and convert the original image into a form that is more suitable for the observation of human eyes and computer analysis.. It is generally based on the visual characteristics of the human eye, to obtain the visual effect of the visual effect, and seldom involves the objective and uniform evaluation criteria.. The effect of the enhancement is usually related with the concrete images, and it is evaluated by the subjective feeling of the person..At present, the application of image enhancement has been penetrated into the medical diagnosis, aviation, military reconnaissance, fingerprint identification, non-destructive testing, satellite image processing and other fields.. Such as X-ray images, CT and endoscopic mirror image enhancement, allow doctors to more easilyidentify the lesion area, from the details of the image region finding problem, taken at different times on the same area of remote sensing image enhancement processing to detect whether the enemy troop movements or military equipment and building; in coal mine industrial TV system with enhanced processing to improve the clarity of industrial TV image, overcome due to the lack of light, dust and other reasons caused by image fuzzy and deviation, reduce TV system maintenance workload. Image enhancement technology rapid development with its wide application is inseparable, the motive force of the development from the emergence of stable new application, we can expect, in the future society image enhancement technology will play a more important role.2 The research status at home and abroadPictures for the first time in the 1920 s through the cable from London to New York. People at that time through the character simulation to get the middle value method to restore the image. Early image enhancement technology often involves hardware parameters Settings, such as the choice of printing process and the distribution of brightness level. At the end of 1921, this paper proposes a new technology based on optical reduction. During this period due to the introduction of a coded modulation beam images to convey to adjust the degree of photographic film, the grey level grayscale increased from 5 to 15 grey scale, this method obviously improved the effect of image restoration. To the early 1960 s first can perform tasks of large computer digital image processing, it marks the use of computer technology the advent of the era of digital image processing. In 1964, researchers at the jet propulsion laboratory (JPL) in the use of computers and other hardware devices, using geometric correction, gray level transformation, noise, such as Fourier transform and 2-d linear filtering enhancement method for space probe \"prowler 7\" back to thousands of Zhang Yueqiu photo processing, at the same time they also consider the influence of the sun and the moon environment, finally succeeded in mapping out the map on the surface of the moon. Then they for 1965 years \"prowler 8\" tens of thousands of photos in the back to earth more complex digital image processing, further improve the image quality. These achievements not only attract the attention of the world many relevant parties and JPL itself also pay more attention to the digital image processing research and improvement of the equipment, and set up the image processing laboratory IPL. Success in the IPL for the hundreds of thousands of photos to spacecraft to send back the more complicated image processing, finally obtained the topography of the moon, color chart, and panoramic Mosaic. From the digital image enhancement technology into the field of aeronautics and astronautics.In the late 1960 s and early 1970 s some scholars began to image enhancementtechnique for medical image, the earth remote sensing monitoring and astronomy, and other fields. X ray is one of the earliest used in imaging of the electromagnetic radiation sources, X-ray by roentgen discovered in 1895. Mr Godfrey n. 1970 s Hounsfield and Allan m. Cormack invented the computer, a professor at axial tomography (ct) technology: a detector around the patient, and X-ray source rotate around the object. X-rays through the body and by the corresponding detector are collected on the other side of the ring. Its principle is to use the data of perception to slice image reconstruction. When objects along the perpendicular to the direction of the detector will produce a series of slices, the section of the internal representation of the object. In the 1980 s, the development of a variety of hardware that makes people not only can deal with 2 d images, and start dealing with three-dimensional images. Many can obtain three-dimensional images of three-dimensional image processing equipment and analysis of the system has been successfully developed, the image processing technology has been widely used. Into the 1990 s, the image enhancement technology has gradually involved in all aspects of human life and social development.A computer program used to enhance the contrast or brightness coding for color, in order to explain X rays, and used in industrial, medical and biological sciences in areas such as other images. Geography with the same or similar technology research pollution mode from the aviation and satellite images. In the field of archaeology fuzzy images using image processing method has been successfully recovered. In the field of physics and related computer technology can enhance experiment in the field of high energy plasma and electron microscope images. Histogram equalization processing is one of the commonly used methods for image enhancement technology. Kim, 1997, if you want to image enhancement technique used in digital cameras and other electronic products, then the algorithm must maintain the brightness of the image features. In the article, Kim keep brightness characteristics of histogram equalization algorithm was presented (BBHE). Kim, the improved algorithm is raised, caused the attention of many scholars. In 1999, Wan subgraph two-dimensional histogram equalization algorithm is put forward by (DSIHE). Then, Chen and Ramli minimum mean square error (MMBEBHE) double histogram equalization algorithm.In order to keep the image features, many scholars to study local enhancement processing technology, many of the new algorithm is proposed: recursion average stratified balanced treatment (RMSHE), recursive subgraph equalization algorithm (RSIHE), dynamic histogram equalization algorithm (DHE), maintain brightness characteristics dynamic histogram equalization algorithm (BPDHE), multi-layer histogram equalization algorithm (MHE), brightness to keep clusters of histogram equalization processing (BPWCHE) and so on.In relatively mature theoretical system and draw lessons from foreign technology under the conditions of application system, enhancement technique and application of domestic also had the very big development. In general, image enhancement technology in the development of its initial stage, development, popularization and application of four stages. Early-stage began in the 1960 s, when the image in pixels type raster scan display, in the USES mostly, mainframe to deal with it. During this period due to image storage cost is high, the processing equipment cost is high, thus its application is very narrow. The entered the period of 1970 s, is used in great quantities in the mainframe processing, image processing is gradually convert raster scan display mode, especially in the CT and satellite remote sensing image, the image enhancement processing put forward a higher request. In the 1980 s, image enhancement technology into the popularization period, the computer has been able to to undertake the task of image processing. Entered the application period in the 1990 s, people use digital image enhancement technology processing and analysis of remote sensing images, in order to effectively resources and mineral resources exploration, investigation, agricultural and urban land planning, crop yield estimation, weather forecast and disaster monitoring and military targets, etc. In biomedical engineering, and using image enhancement technique of X-ray images, ultrasound images, and biological section microscopic image processing, such as to improve image clarity and resolution. In industrial and engineering, mainly used in nondestructive flaw detection, automatic quality inspection and process control, etc. In public security, portraits, processing and identification of fingerprints and other trace, and traffic monitoring, accident analysis using image enhancement technology in different extent.Image enhancement is an important part of image processing, the traditional image enhancement method plays a very important role to improve image quality. With the deepening of the research of image technology and development, a new image enhancement method appear constantly. For example, some scholars will be introduced to the theory of fuzzy mapping image enhancement algorithms, including fuzzy relaxation, fuzzy entropy is proposed, fuzzy enhancement algorithm to solve the problem of enhancement algorithm of mapping function selection, and with the application of interactive image enhancement technology, can control the subjective image enhancement effect. And image enhancement using histogram equalization technology has many new progress, such as multilayer histogram combined with a balanced of brightness algorithm is proposed, dynamic hierarchical histogram equalization algorithm. These algorithms by image segmentation, and then in the sub-layer do balance in image processing, better solve the contrast through stretching problem in the process of histogram equalization, and it can control sub-layer gray mapping scope, strengthen effect is better.3 Key technology (method) is introducedImage enhancement can be divided into two categories: frequency domain and spatial domain method. The former the image as a two-dimensional signal, based on the two-dimensional Fourier transform to signal enhancement. Using low pass filter (that is, only through low frequency signal) method, can get rid of the noise in the graph; Using the high-pass filtering method, can enhance the high frequency signal, such as the edge, the fuzzy image becomes clear. The latter is the typical algorithms in spatial domain method with local averaging method and median filter (in the middle of the field of local pixels) method and so on, they can be used to remove or less noise. Image enhancement method is to through certain means for additional information or to transform of the image data, particularly interested in the image features or selectively inhibit (hide) the image features, some don't need to match the images and visual response. In the process of image enhancement, not this paper analyzes the reasons of images is qualitative, not necessarily close to the original image after processing. Image enhancement technology based on the enhanced processing in space is different, can be divided into the airspace based algorithm and based on frequency domain algorithm two kinds big. Based on the algorithm of the airspace to handle directly do arithmetic of image grayscale, based on the algorithm of frequency domain is in a transform domain of the image to some correction, image transform coefficient value is a kind of indirect enhancement algorithm.Algorithm based on airspace is divided into the neighborhood denoising arithmetic algorithm and algorithm. Algorithm namely grayscale correction arithmetic, such as gray transform and histogram modification, purpose or for uniform image imaging, or expand the dynamic range image, expand the contrast. Neighborhood enhancement algorithm into image smoothing and sharpening two kinds. Smooth generally used to eliminate image noise, but also easy to cause the edge of the fuzzy. Commonly used algorithm with average filtering and median filtering. Sharpen the purpose is tohighlight the edge contour of the object, is advantageous for the target identification. Commonly used algorithm with gradient method, operator, high-pass filtering, mask matching method, statistical difference method, etc.4 conclusionOf image enhancement technology is introduced, through this homework, made me more solid grasp the related knowledge of machine vision, while in the process of finish this assignment have a few problems, but after thinking again and again, and again and again on the Internet to collect related material and finally to solve all problems.From the beginning a little knowledge of image enhancement technology to the understanding of image enhancement technology now, I paid a lot of effort. Through the consult relevant material in the library and online collection of various learning summary of the material, make me to have a deeper understanding of image enhancement technology, machine vision for this course have a deeper understanding.I think, in the operation, not only cultivate my independent thinking and the ability of collecting data, in a variety of other skills have improved. And, more importantly, in the process of operation, I learned a lot of learning method, which is the most practical in the future, really benefit a lot. To face the challenge of the society, only by constantly learning, practice, learning and practice. It also has a lot of help for our future. Later, no matter how bitter, I think we can become a pain for a pleasure, looking for fun, find it precious things. Problems encountered in the process of homework, have to be difficult, so to speak, but the good news is that eventually solved.This assignment also let I see, have what not understand don't understand to consult or surf the Internet query in time, as long as study earnestly, people think, hands-on practice, can't understand the knowledge, harvest quite abundant.In a word, take every chance to learn seriously, cherish every point inthe process of a second, learn the knowledge and method of most, exercise their power, this is we are in the work the most important thing you have learned, later will also benefit a lot!参考文献[1] ×××.××××××××××××××××××××××××××××××××××[2] ×××.××××××××××××××××××××××××××××××××××。