Optimized Image Compression for Mobile Photography
Abdellah El Mennaoui, Ghalia Hemrit, Jean‐Luc Dugelay · 2025
The widespread adoption of smartphones with high-resolution cameras has driven a surge in image capture, particularly for selfies, food, and landscapes, which dominate social media. Efficient image compression is essential to reduce storage and transmission requirements while maintaining visual quality. Traditional methods like JPEG and JPEG2000 have reached their limits, making learning-based image compression (LIC) a promising alternative. However, most LIC models, such as SegPIC [2], are trained on general-purpose datasets like COCO, limiting their effectiveness for smartphone-specific content.