Payload location using residuals is a successful approach to identify load-carrying pixels provided a large number
of stego images are available. Furthermore, each image must have the payload embedded at the same locations.
The success of payload location is therefore limited if different keys are used or an adaptive embedding algorithm
is used. Given these limitations, the focus of this paper is to locate modified pixels in a single stego image.
Given a sufficiently large set of independent binary decision functions, each determines whether a pixel has been
modified better than guessing, we show that it is possible to locate modified pixels in a single stego image with
low error rate. We construct these functions using existing cover estimators and provide experimental results to
support our analysis.