图像增强技术：原理、分类与性能评价

"Abstract Image enhancement refers to the process of highlighting certain information in an image, while simultaneously reducing or removing redundant information based on specific needs. Its main goal is to make the enhanced image more effective for a given application compared to the original image and to improve image quality. Image enhancement techniques include histogram modification, image smoothing, sharpening, and color enhancement. Image enhancement can be broadly categorized into two main types: frequency domain methods and spatial domain methods. Spatial domain algorithms are further divided into point operation algorithms and neighborhood denoising algorithms. Point operation algorithms include grayscale correction, grayscale transformations, and histogram equalization, which aim to make images appear more uniform, or to expand the dynamic range and contrast. Neighborhood enhancement algorithms include image smoothing and sharpening. Smoothing is commonly used to eliminate image noise, but can also cause edge blurring. Sharpening aims to highlight object edges for easier recognition. This paper provides an overview of image enhancement principles, categorizes image enhancement methods, and introduces several commonly used enhancement techniques such as histogram enhancement, contrast enhancement, smoothing, and sharpening. The theory of color image enhancement is also discussed. Practical experiments using MATLAB are conducted to compare the effectiveness of different algorithms, discuss the strengths and weaknesses of various enhancement techniques, and evaluate the performance of image enhancement methods. Keywords: Image enhancement; Histogram; Smoothing; Sharpening"