The thesis explores the diverse landscape of raster image file formats, highlighting the need for informed selection beyond older, established options like JPEG and PNG. It analyzes the technical underpinnings and performance characteristics of various formats, including newer ones like WebP, AVIF, and JpegXL, considering factors like compression efficiency, visual quality, and encoding/decoding speed. The research conceptualizes a desktop software application designed to empower users with data-driven decisions for image format selection, allowing comparison based on criteria like target image quality, file size, or fixed settings, visualizing the trade-offs to help users optimize their image handling for better resource management and enhanced digital experiences.