Memory-Friendly Image Processing

Large assets ke saath kaam karte waqt browser memory ceiling ko respect karna zaroori hai. Yeh habits stability improve karti hain.

Habits

• Preview downsized
• Process in workers
• Chunked operations

Why browsers struggle

Decoding + canvas operations memory heavy hote hain (width × height × channels). Multiple copies (original, working, preview) quickly GBs touch kar sakte hain. Isliye streaming/tiling se footprint kam rakhein.

Techniques that work

• Tiled processing for huge images
• Transferable objects between workers
• Release references ASAP (null out blobs)
• OffscreenCanvas for background work

Practical tips

• Preview at 25–50% scale
• Limit concurrent jobs
• Use WebP/AVIF decoding over raw bitmaps when possible

Case studies

Gigantic panoramas

Tiles @ 1024×1024 process; memory peaks −60%, no crashes.

Bulk PDF page renders

Sequential page queue + thumbnail previews; UX smooth, memory stable.

Wrap‑up

Stable sessions = faster teams. Memory‑smart pipelines long runs me time save karte hain.