This paper presents a novel rotation estimation approach based on 3D mesh representation of spherical images. Indeed, unit sphere is becoming a natural space for projecting images captured from the central cameras (conventional and non-conventional cameras, as omnidirectional camera) and obtaining the spherical images. The proposed method relies on representing the spherical images into a 3D space based on image intensities. Spherical harmonic coefficients are then calculated for the 3D mesh surfaces and used to estimate an initial rotation between the underlying spherical images in spectral domain. The optimal rotation is then refined through the ICP algorithm. Experimental results, using synthetic and real image dataset, demonstrate the effectiveness of the proposed approach for rotation estimation, as well as its robustness against real conditions and images occlusion. A comparison between the proposed method and competitive ones, is performed.