AI BriefingOptimizing Image Processing with Web Worker
Key point
This covers the process of solving main thread load and UI degradation issues that occur when processing high-resolution images in Oliveyoung's Shutter service, by introducing Web Worker.
Details
Oliveyoung's community service, Shutter, has high-quality image upload as a core feature. However, in mobile environments, when processing high-resolution images of 4MB or more, excessive browser memory usage and main thread blocking caused UI responsiveness to degrade or forced the browser to refresh.
Previously, format conversion (WebP) or resizing using Canvas was attempted, but due to the CPU-intensive nature of these operations, they also occupied the main thread, causing UX degradation such as click event delays. In particular, when the network environment was unstable, user complaints and resource waste due to large data transfers were intensified.
To solve this, Web Worker was introduced. Since Web Worker operates on a background thread separate from the main thread, it can process CPU-intensive tasks that don't require DOM access, such as decoding, resizing, and format conversion, in parallel.
Among the various types of Workers, a Dedicated Worker, which is optimized for 1:1 communication and data processing on a single page, was used to build a stable image upload environment while maintaining UI responsiveness.
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