An image processing system is a combination of hardware, software, data, algorithms, and human expertise used to acquire, process, analyze, store, and display digital images. In geoinformatics and disaster management, image processing systems are fundamental for extracting valuable information from satellite imagery, aerial photographs, drone images, and other remote sensing data. These systems support hazard mapping, damage assessment, emergency response, and recovery planning. The first component is image acquisition. It involves capturing images using sensors mounted on satellites, aircraft, drones, or ground-based platforms. These sensors record electromagnetic radiation reflected or emitted from the Earth's surface. The quality of acquired images depends on factors such as spatial, spectral, radiometric, and temporal resolution. Image acquisition also includes converting analog signals into digital format through sampling and quantization. The second component is image sensing devices. These include optical sensors, multispectral sensors, hyperspectral sensors, thermal sensors, microwave sensors, and Synthetic Aperture Radar (SAR). Different sensors provide information suitable for monitoring floods, earthquakes, cyclones, droughts, forest fires, landslides, and other disasters under varying weather and lighting conditions. The third component is specialized image processing hardware. High-performance computers, Graphics Processing Units (GPUs), digital signal processors, and dedicated image processing workstations enable rapid execution of computationally intensive operations. Such hardware is essential for processing large volumes of remote sensing data during emergency situations. The fourth component is image processing software. Software packages such as ERDAS