Image Enhancement Using Improved Laplacian Pyramid and Unsharp Masking Methods

In this article, I will provide a detailed introduction to an image enhancement algorithm developed in MATLAB that combines improved methods of Laplacian Pyramid decomposition and unsharp masking. This algorithm is designed to enhance image quality, making images clearer and more easily recognizable. First, we will explore the concept of Laplacian Pyramid decomposition and its applications in image processing, including its implementation using MATLAB's pyramid functions for multi-scale analysis. We will then introduce the principles of unsharp masking and how it contributes to image enhancement by emphasizing high-frequency components through convolution operations with specific kernel parameters. Following this, we will discuss in detail how to integrate these two methods to achieve superior image enhancement results, focusing on algorithmic improvements such as adaptive thresholding and multi-scale fusion techniques. Finally, we will demonstrate the algorithm's practical applications through concrete examples, including implementation code snippets showing key functions like impyramid for pyramid construction and imfilter for mask application, to better understand both the advantages and limitations of this approach in various image processing scenarios.