Replacing DWT with DTCWT in blind image rotation angle estimation

Abstract

During the image tampering, rotation is often involved to make the forgery more convincing. Hence, estimating the rotation angle accurately and locally is of forensic importance. Recently, a novel rotation angle estimation scheme was proposed based on linear pattern (LP), achieving state of the art performance especially in the case when the rotation angle is small. However, due to the limitations of the involved discrete wavelet transform (DWT), the existing LP based method cannot always accurately detect rotated linear pattern from a rotated image. To fill this gap, we propose to extract the rotated LP using dual tree complex wavelet transform (DTCWT). Thanks to the good directional selectivity of DTCWT, the proposed method can extract the LP more accurately. Experiments show that our proposed method performs better than the state of the art in rotation angle estimation, and is also a promising forensic tool for tampering localization.