图像锐化算法研究与仿真：MATLAB实现及优化方法对比分析

With the advancement of technology, the quality of images may degrade due to various factors. Image enhancement aims to selectively highlight information that is of interest for analysis by humans or machines, while suppressing irrelevant information, in order to improve the usability of the image. Image sharpening is a type of spatial domain local operation method in image enhancement, with the goal of enhancing and emphasizing the edge and contour information of the image. The specific method of image sharpening involves enhancing and sharpening the edges of the image through differentiation. The most commonly used method for image sharpening is the gradient sharpening method. In addition to gradient algorithms, there are also various other methods for image sharpening, such as Roberts, Prewitt, Sobel, and Laplacian algorithms. This paper introduces, compares, and analyzes these methods. Finally, an introduction to MATLAB is provided, and some image sharpening algorithms are implemented using MATLAB language, with results recorded. Through simulation and comparison of various algorithms, each method has its own advantages and disadvantages. After analyzing the characteristics of the images used in this study, an improvement was made to the Laplacian algorithm by using high-boost filtering to enhance the brightness of the image. Experimental results demonstrate that this method is feasible and achieves the desired sharpening effect. In conclusion, image sharpening is an important aspect of image enhancement, and different algorithms have their own strengths and weaknesses. By understanding the characteristics of the images being processed and making targeted improvements to algorithms, it is possible to achieve better results in image sharpening. Keywords: Image enhancement; Edge; MATLAB; Image sharpening.