MATLAB Code Implementation for Linear Equation Solutions with SVD-Based Motion Target Detection

In this paper, we provide a detailed explanation of linear equation solutions and demonstrate their application in moving target detection. Specifically, we focus on addressing background suppression and noise reduction challenges in visible light image weak target detection by proposing a Singular Value Decomposition (SVD)-based approach. We introduce the fundamental principles and applications of SVD, along with MATLAB implementation details for processing noise and background issues in visible light images. The implementation includes key functions such as svd() for matrix decomposition and appropriate thresholding techniques for separating targets from background. Furthermore, we discuss practical application cases of SVD and provide comprehensive guidance on implementing these solutions in real-world scenarios. The paper covers algorithm optimization techniques including rank reduction and eigenvalue thresholding for efficient computation. Thus, this work offers a complete understanding of SVD technology and practical implementation strategies for solving real-world detection problems through MATLAB code examples and performance analysis.