Research On Image Enhancement And Edge Detection Algorithm Based On Visual Characteristics

It is an important part of image processing about image enhancement and edge detection technology.Image enhancement algorithm can enhance the detail information people want in the image.It can make the image have better visual sense and higher contrast.It is a very important step about edge detection in image processing,which plays a very important role in the subsequent image processing,such as the in-depth description of the image features,information recognition or matching.Therefore,it is of great significance about the research of image enhancement and edge detection technology.With the development of image processing technology,some scholars have studied the image enhancement or edge detection algorithm based on the vision characteristics of human eyes.Through the continuous efforts of scholars,great achievements have been made.However,so far,a widely recognized algorithm has not been obtained,and the limitations and defects still exist.Such as,some scholars have only combined the structural features of the human eye and some only combine the gray features of the human eye.Some scholars combine more comprehensively,but the algorithm is more complicated.Therefore,in the field of image processing,it is still a hot research topic that how to combine the visual characteristics of the human eyes to study image enhancement or edge detection algorithm.In view of the above problems,a new method of calculating the threshold is realized in this dissertation,which comprehensively combines the visual characteristics of the human eye,and analyzes the algorithms of image enhancement,edge detection and edge thinning combined with the threshold value calculated by the method.The main work of this dissertation is as follows:First of all,we summarize the image enhancement and edge detection algorithms that commonly used at home and abroad,and analyze and compare their advantages and disadvantages.Through the analysis,we comprehensively combines the visual characteristics of the human eyes in this dissertation to realizes a new method of calculating the threshold and explain the rationality of the threshold.Secondly,an image enhancement algorithm based on human eye vision features has been realized based on the research of the relevant scholars and combining the new threshold realized in this dissertation.Through the simulation experiment using MATLAB software,the experimental results of the algorithm are analyzed and compared with the traditional image denoising algorithm,the traditional image enhancement algorithm and the image enhancement algorithm of the relevant scholars.The experimental results show that the algorithm realized in this dissertation not only can enhance the visual effect of the image,but also able to effectively suppress the image noise.Besides,this algorithm can also enhance and protect the details of images,such as edges and corners.Finally,aiming at the shortcomings of the traditional Robert edge detection operator,an improved Robert edge detection algorithm is proposed based on the human visual characteristics.This algorithm not only has a good function to suppress noise,but also can gets a more delicate and smooth image edge.In view of the shortcomings of the traditional edge detection algorithms of Prewitt and Kirsch,such as high complexity and poor denoising ability,it is based on the visual characteristics of human eyes to analyze and improve their ability to suppress noise and reduce the complexity of the algorithm of Prewitt.In order to solve the problem of high complexity of the traditional edge thinning algorithm,it is analyzed in this dissertation about the principle of the original algorithm to reduces the complexity of the original algorithm and optimizes the original algorithm.