Enhanced Image Enhancement Algorithm Integrating Laplacian Pyramid and Unsharp Masking Techniques

This article presents a MATLAB-based image enhancement algorithm that integrates Laplacian Pyramid decomposition with an improved unsharp masking approach. The Laplacian Pyramid serves as a multi-resolution image processing technique that decomposes an image into multiple hierarchical levels, where each level corresponds to specific frequency components within the image. The unsharp masking technique enhances image quality by strategically reducing sharpening artifacts while preserving important edge information.

By synergistically combining these two methodologies, we achieve more efficient and precise image enhancement. The algorithm not only improves image clarity and contrast but also effectively reduces noise and blurring artifacts. This makes it particularly valuable in digital image processing applications such as medical imaging, remote sensing, and security surveillance systems.

The implementation leverages MATLAB's image processing toolbox, utilizing functions like impyramid() for pyramid decomposition and imfilter() for mask operations. The algorithm structure allows for customizable parameter adjustments including pyramid levels, mask sizes, and enhancement coefficients through configurable input parameters. This ensures excellent portability and scalability, enabling researchers to perform customized developments according to specific application requirements.