Image Compression Compared: Formats, Quality Settings, and File Size Realities | GoToolstack
Compare JPEG, WebP, and PNG compression realities. Real measurements from browser Canvas encoding, quality loss trade-offs, and transparency limitations.
Selectively blur or pixelate sensitive faces, license plates, and private text in photos.
Client-Side Privacy Blur Tool obscures sensitive visual elements—including human faces, automotive license plates, street addresses, and credit card numbers—directly inside the browser before sharing photos publicly. Utilizing Canvas 2D image filtering and convolution kernels, it applies localized blur or mosaic pixelation without sending unblurred images across the internet.
The interface enables interactive bounding box selection: users draw rectangular masks directly over sensitive areas on the image canvas. A granular blur intensity slider controls the convolution radius from subtle softening up to heavy geometric mosaic pixelation. As an added privacy safeguard, the export engine automatically scrubs all EXIF metadata, camera serial numbers, and embedded GPS geolocation coordinates during file generation.
Concrete Scenario: An investigative journalist takes a street photo (3000x2000 JPG, 3.4 MB) showing bystander faces and a vehicle license plate. Dragging two rectangular masks over the faces and one over the plate with a 24px pixelation radius permanently obscures identifying features in 80 milliseconds. Downloading the sanitized image yields a clean 1.1 MB JPEG with zero embedded geolocation tags.
Because image convolution, pixel neighborhood averaging, and metadata eradication occur entirely within local browser memory, sensitive journalistic sources, private residential exteriors, and family photographs remain protected.