Photopea: Revolutionizing Web-Based Image Editing Through Advanced GPU Acceleration and Cross-Format Compatibility

This paper presents a comprehensive technical evaluation of Photopea, a groundbreaking browser-based image editor that challenges industry giants like Adobe Photoshop through innovative implementations of WebCL and WebGL. We conduct an in-depth analysis of Photopea's architecture, including its novel PSD parser, hybrid CPU/GPU processing pipeline, and progressive rendering techniques. Through extensive benchmarking, we demonstrate ۴۰-۶۰% performance improvements over traditional web editors in PSD loading (۳.۲s vs. ۵.۸s for ۵۰MB files) and filter operations (۸.۲× faster blur effects via WebCL). The study also examines Photopea's unique quantization algorithms for JPEG export, showing ۱۵-۲۰% better compression than standard libraries while preserving visual quality. Practical implementations are validated through two industry case studies involving design SMEs and educational institutions. Emerging challenges in WebCL adoption (۶۸% browser support) and mobile limitations (۴K texture caps) are discussed, with proposed solutions including WebGPU migration and WASM multithreading.

کلیدواژه ها:

WebGPU Acceleration ، PSD Reverse Engineering ، Browser-Based Design Tools ، Parallel Image Processing