Implementation of Basic Image Processing Algorithms

This article provides detailed MATLAB implementations of fundamental image processing algorithms, covering essential techniques such as edge extraction methods and ROC (Receiver Operating Characteristic) analysis. For each algorithm, we present comprehensive implementation approaches including key MATLAB functions like edge() for Sobel/Canny detection, imgradient() for gradient computation, and perfcurve() for ROC analysis. The step-by-step explanations include algorithm principles, parameter optimization techniques, and code structure organization. We'll demonstrate practical implementation details such as convolution kernel design for edge operators, threshold selection strategies, and performance metric calculations. Additionally, we explore real-world application scenarios and discuss each algorithm's advantages and limitations in practical implementations, including computational efficiency considerations and accuracy trade-offs. Through this comprehensive guide, you'll gain deep understanding of these core image processing algorithms, establishing a solid foundation for future research and professional applications.