Digital Image Enhancement And Its Realization

Modern scientific research in various fields, military technology, industrial and agricultural production, medicine, meteorology, electronic technology, the image information is used more and more people are understanding and judgment of things, solve practical problems. Among the practical life, the image obtained by the imaging system will have a certain degree of degradation, resulting in the loss of image information. Under conditions of low visibility in the scene captured image contrast and colors are changed in the foggy weather or degraded images contain many of the features are covered or blurred, so that the scene can greatly reduce the degree of recognition, which requires image enhancement and recovery technology to improve people’s visual effects. The typical image processing system consists of three phases, the first is to get the original image preprocessing:Second feature extraction stage; Third, recognition analysis phase. Image pre-processing is particularly important at this stage if not handled properly, the follow-up work will not be started. The image pre-processing digital image enhancement is an important technique, showing its importance. Image enhancement purpose is to improve the visual effect of the input image to become blurry images sharp images, so as to lay a solid foundation for subsequent image analysis and image understanding links.Currently at home and abroad, image enhancement processing technology has had a wide range of important applications in medical diagnostics, aerospace, military reconnaissance, fingerprint identification, satellite images and other fields, so the research it has very important significance. Image enhancement methods are often targeted, it is difficult to quantify the results described in enhancing rely on experience to people’s subjective evaluation of a number of domestic and foreign scholars have proposed enhancement algorithms, but so far no one is generic, reliable measure of image quality indicators to evaluate the merits of image enhancement methods.Common image enhancement method is divided into spatial domain method and frequency domain method. Spatial domain method is the direct method, frequency domain method called indirect method. Spatial domain image enhancement method is pixel image processing, can be defined, g(x,y)=T[f(x,y)], where in the input image f(x,y) is the original image, the output image g(x,y), i.e., after the image processing of an operation. Common spatial domain image enhancement methods, gray transform, histogram equalization, histogram specification, image smoothing, image sharpening.Frequency-domain image enhancement method is to image the first Fourier transform to the frequency domain, in a variety of image filtering to process images. The basic steps are:①Calculation of the Fourier transform of the need to enhance the image;②it with one (according need to design) transfer function convolution;③the inverse Fourier transformation results in enhanced image. Filters used with ideal (high) low-pass filter, Butterworth (high) the low-pass filter, Gaussian (high) low pass filter.This paper discusses a method of digital image enhancement and implementation of image enhancement purpose is to improve the visual quality of the image. Spatial domain method and frequency-domain method has been studied very thoroughly, and the method of using a single image processing image enhancement effect is not very obvious, so this article will introduce an image enhancement method spatial domain and frequency domain binding, and proposed two space domain and frequency-domain combination of image enhancement methods. For image enhancement technology, this paper introduces the purpose and significance of image enhancement, background image enhancement technology development research at home and abroad as well as its application in the actual production. Then this paper introduces the basic theory of digital image processing knowledge in this discipline, so that readers understand some of the terminology on this discipline, the discipline of a clear understanding clearly the main research content of this discipline. Then this article will deal with this piece of image enhancement gives some theoretical knowledge, including image enhancement principle, there are some technical terms and so on. Then again, this article will be a variety of traditional image enhancement image enhancement method one by one to explain, including spatial and frequency domain, this section will be divided into two chapters to explain, and all Matlab programming to achieve each simulation kinds of image enhancement algorithms for image processing effects. Then by analyzing the characteristics of the traditional methods of image enhancement, the study on the basis of the traditional methods, this paper presents two methods of image enhancement spatial domain and frequency domain image enhancement method combined, and by Matlab simulation of these two algorithms simulation. A first image enhancement algorithm of histogram equalization in the spatial domain, the Gaussian low pass filter in the frequency domain and the Laplace transform of the combined histogram equalization is discussed, and the Laplace transform of Gaussian low-pass filtering the basic principle of de-noising for image noise using a frequency domain denoising in the spatial domain histogram equalization method of enhancing and sharpening and use some objective indicators to illustrate the effectiveness of this method of image enhancement. The experimental results show that this method can make the image clearer, more sharpening. The second algorithm histogram equalization and spatial domain to the frequency domain Gaussian high-pass filter to filter based on a combination of high frequency boost. Histogram equalization is a classic and effective means for image enhancement, but the processed image of a large loss of gray levels, and enhanced enough. High boost filtering high frequency components of the image can be enhanced, that the details of the image to compensate for the lack of histogram equalization method. In this paper, the spatial domain and frequency domain histogram equalization combining high boost filtering method for image processing. Dramatic changes in the use of image information with high frequency components only on this principle, combined with MATLAB program design, implementation and histogram equalization processing image enhancements, and then use high boost filtering on the basis of image processing. Experimental results show that this method enhanced the image by its significantly improved subjective visual effects, image enhancement using a technique than a single effect is better.In this paper, an image enhancement method to do a full in-depth research, I hope the readers of this knowledge in the learning image enhancement when there is some help, specifically includes:1understand the basic theoretical knowledge of digital image processing;(2) a detailed description of digital image enhancement technology;3introduces traditional digital image enhancement methods;4presents two new image enhancement algorithm:①a frequency domain and space domain based on the combination of image enhancement,②Based on high boost filtering and histogram equalization image enhancement method;5programming all digital image enhancement method proposed;...