Search

Just noticeable distortion (JND), representing the threshold of distortion in an image that is minimally perceptible to the human visual system (HVS), is crucial for image compression algorithms to achieve a trade-off between transmission bit rate and image quality. However, traditional JND prediction methods only rely on pixel-level or sub-band level features, lacking the ability to capture the impact of image content on JND. To bridge this gap, we propose a Semantic-Guided JND (SG-JND) network to leverage semantic information for JND prediction. In particular, SG-JND consists of three essential modules: the image preprocessing module extracts semantic-level patches from images, the feature extraction module extracts multi-layer features by utilizing the cross-scale attention layers, and the JND prediction module regresses the extracted features into the final JND value. Experimental results show that SG-JND achieves the state-of-the-art performance on two publicly available JND datasets, which demonstrates the effectiveness of SG-JND and highlight the significance of incorporating semantic information in JND assessment., Comment: Accepted by ICIP 2024

We theoretically investigate the engineering of two-dimensional second-order topological insulators with corner states by coupling two first-order topological insulators. We find that the interlayer coupling between two topological insulators with opposite topological invariants results in the formation of edge-state gaps, which are essential for the emergence of the corner states. Using the effective Hamiltonian framework, We elucidate that the formation of topological corner states requires either the preservation of symmetry in the crystal system or effective mass countersigns for neighboring edge states. Our proposed strategy for inducing corner state through interlayer coupling is versatile and applicable to both $\mathbb{Z}_2$ topological insulators and quantum anomalous Hall effects. We demonstrate this approach using several representative models including the seminal Kane-Mele model, the Bernevig-Hughes-Zhang model, and the Rashba graphene model to explicitly exhibit the formation of corner states via interlater coupling. Moreover, we also observe that the stacking of the coupled $\mathbb{Z}_2$ topological insulating systems results in the formation of the time-reversal invariant three-dimensional second-order nodal ring semimetals. Remarkably, the three-dimensional system from the stacking of the Bernevig-Hughes-Zhang model can be transformed into second-order Dirac semimetals, characterized by one-dimensional hinge Fermi arcs. Our strategy of engineering second-order topological phases via simple interlayer coupling promises to advance the exploration of higher-order topological insulators in two-dimensional spinful systems.

We theoretically find that the second-order topological insulator, i.e., corner states, can be engineered by coupling two copies of two-dimensional $\mathbb{Z}_2$ topological insulators with opposite spin-helicities. As concrete examples, we utilize Kane-Mele models (i.e., graphene with intrinsic spin-orbit coupling) to realize the corner states by setting the respective graphenes to be $\mathbb{Z}_2$ topological insulators with opposite intrinsic spin-orbit couplings. To exhibit its universality, we generalize our findings to other representative $\mathbb{Z}_2$ topological insulators, e.g., the Bernevig-Hughes-Zhang model. An effective model is presented to reveal the physical origin of corner states. We further show that the corner states can also be designed in other topological systems, e.g., by coupling quantum anomalous Hall systems with opposite Chern numbers. Our work suggests that interlayer coupling can be treated as a simple and efficient strategy to drive lower-order topological insulators to the higher-order ones.

We propose a general principle for realizing second-order topological corner states in the modified Kane-Mele model with magnetization. It is demonstrated that the sign of the edge Dirac mass depends on the magnetization of the edge sublattice termination. By adjusting the directions of magnetization according to the type of sublattice at the termination of two edges, a mass domain wall can be induced in the presence of topological corner states at an arbitrary position. All previous work on introducing magnetization in the Kane-Mele model to realize second-order topological corner states can be explained by the presence of the Dirac mass domain wall with opposite signs. Applying this principle, we design square-shaped and armchair-type hexagon-shaped graphene nanoflakes with edge magnetization, allowing for the emergence of second-order topological corner states. Our findings serve as a general theory, demonstrating that the realization of second-order topological corner states is not limited by boundary type or nanoflake shape.