Camera Identification from HDR Images
Morteza Darvish Morshedi Hosseini, Miroslav Goljan · 2019
Performance of camera identification methods based on PRNU is very sensitive to geometric operations applied to images during acquisition and processing. Handling images that have been geometrically transformed, such as rotated, downsampled, and/or cropped requires overcoming pixel desynchronization problem. This work expands applicability of camera identification methods based on PRNU to the class of HDR images. Geometric transformations in HDR images revealed in this work are reversed in a series of steps involving block-wise PRNU matching. Efficiency of this method is then tested on HDR images from publicly available UNIFI dataset spanning 26 cameras of mobile devices.