Forensic Detection of Inverse Tone Mapping in HDR images
Abstract
High dynamic range (HDR) imaging is attracting an increasing deal
of attention in the multimedia community, yet its forensic problems
have been little studied so far. This paper proposes an HDR image
forensic method, which aims at differentiating HDR images created
from multiple low dynamic range (LDR) images from those created
from a single LDR image by inverse tone mapping. For each kind
of HDR image, a Gaussian mixture model is learned. Thereafter,
an HDR image forensic feature is constructed based on calculating
the Fisher scores. With comparison to a steganalytic feature and a
texture/facial analysis feature, experimental results demonstrate the
efficiency of the proposed method in HDR image forensic classification
on whole images as well as small blocks, for three inverse tone
mapping methods.