#Redacted picture code

#Redacted picture code

Multiple camera shots, each leaking different information that can be combined (see the BTC QR code story).

Missing blur in the first/last frame after/before a cut.

Unblurred reporter's email address which could also be used to retrieve the previously blurred result page (and cyber bully her?) (the black box was added by me)

Gaussian blur (or similar): Using a specific kernel, the new color of every pixel is influenced by its surrounding pixels (via a weighted average).

Mosaic/Pixelization/Box Linear Filter: Multiple pixels are merged to a bigger one with the color being the average of the original pixel values.

Instead of removing all information for a particular region, here the information density is only reduced.īlurring is usually achieved using one of the following two methods: This technique however does not work for simple image formats that only store one layer of pixel information (except for surprising edge cases when using transparency).Ī popular alternative to redacting information with a colored box is blurring. As text and objects/images in those files are stored as different objects in 'separate layers', redacted text can sometimes still simply be copied, and colored boxes that were intended to hide information can often be removed to reveal the redacted content.

One of the best known attacks on digital redaction methods works only on specific file formats, e.g.

In this blog post, I'll discuss image/video blurring methods and their weaknesses and present a simple yet effective method to get a high-resolution image from a pixelated video in order to recover redacted information (with no guessing involved). It's therefore no wonder that some people might have a motivation to try to reverse such a redaction for various reasons. Information that has been redacted is often the most interesting.