Platform Independent Satellite Image Processing Using GPGPU

The volume of multimedia data is increasing in areas such as big data analytics, image processing, and computer vision, making it challenging to interpret and use information efficiently. Traditional methods for processing such data need a lot of time and resources. The proposed system seeks to identify significant changes in environmental parameters using various image processing techniques while allowing hardware and operating system independence. This study suggests the use of parallel programming frameworks like CUDA and OpenCL to develop a system for analyzing satellite images. This includes a performance benchmarking analysis between traditional and parallel implementations. The proposed system has the potential to be time and energy efficient while giving scientists, planners, and decision-makers access to a variety of valuable data for effective policy and decision-making. Change detection in satellite images is a key application area of the proposed system.