Infrared Image Enhancement and Target Detection Demo Interface

During my master's thesis research, I independently designed and developed an infrared image enhancement and target detection demonstration interface. The interface features an intuitive GUI (Graphical User Interface) built using MATLAB's App Designer, allowing users to perform interactive demonstrations of infrared image processing algorithms. Through this platform, users can explore the underlying principles and methodologies of infrared image enhancement techniques (such as histogram equalization, contrast stretching, and noise reduction filters) and target detection algorithms (including morphological operations, threshold-based segmentation, and feature extraction). The interface incorporates real-time processing capabilities where users can adjust parameters like contrast levels, threshold values, and filter kernels while immediately observing the computational results. The design prioritizes user experience with logical workflow organization and responsive controls, making operations straightforward and efficient. Additional functionalities include image export capabilities supporting multiple formats (PNG, JPEG, TIFF) and customizable parameter presets for different scenarios. The backend implementation utilizes optimized matrix operations for efficient image processing and employs callback functions for seamless interaction between GUI components and processing modules. This demonstration interface represents a significant achievement from my master's research, effectively showcasing my technical contributions and providing an educational tool for explaining complex image processing concepts through practical implementation examples.