Towards Robust Rain Removal with Unet

Image deraining has become a hot topic in the field of computervision. It is the process of removing rain streaks from an image to reconstructa high-quality background. This study aims at improving the performance ofimage rain streak removal and reducing the disruptive effects caused by rain.To better fit the rain removal task, an innovative image deraining method isproposed, where a kernel prediction network with Unet++ is designed andused to filter rainy images, and rainy-day images are used to estimate thepixel-level kernel for rain removal. To minimize the gap between synthetic andreal data and improve the performance in real rainy image handling, a lossfunction and an effective data optimization method are suggested. In contrastwith other methods, the loss function consists of Structural Similarity Indexloss, edge loss, and L1 loss, and it is adopted to improve performance. Theproposed algorithm can improve the Peak Signal-to-Noise ratio by 1.3% whencompared to conventional approaches. Experimental results indicate that theproposed method can achieve a better efficiency and preserve more imagestructure than several classical methods.

A Reversible Data Hiding Algorithm Based on Image Camouflage and Bit-Plane Compression

Reversible data hiding in encrypted image(RDHEI)is a widely used technique for privacy protection,which has been developed in many applications that require high confidentiality,authentication and integrity.Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image.Moreover,the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers.This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression.A camouflage encryption algorithm is used to transform a secret image into another meaningful target image,which can cover both secret image and encryption behavior based on“plaintext to plaintext”transformation.An edge optimization method based on prediction algorithm is designed to improve the image camouflage encryption quality.The reversible data hiding based bit-plane level compression,which can improve the redundancy of the bit plane by Gray coding,is used to embed watermark in the camouflage image.The experimental results also show the superior performance of the method in terms of embedding capacity and image quality.

Topology optimization of compliant adaptive wing leading edge with composite materials

An approach for designing the compliant adaptive wing leading edge with composite material is proposed based on the topology optimization. Firstly, an equivalent constitutive relationship of laminated glass fiber reinforced epoxy composite plates has been built based on the symmetric laminated plate theory. Then, an optimization objective function of compliant adaptive wing leading edge was used to minimize the least square error（LSE） between deformed curve and desired aerodynamics shape. After that, the topology structures of wing leading edge of different glass fiber ply-orientations were obtained by using the solid isotropic material with penalization（SIMP） model and sensitivity filtering technique. The desired aerodynamics shape of compliant adaptive wing leading edge was obtained based on the proposed approach. The topology structures of wing leading edge depend on the glass fiber ply-orientation. Finally, the corresponding morphing experiment of compliant wing leading edge with composite materials was implemented, which verified the morphing capability of topology structure and illustrated the feasibility for designing compliant wing leading edge. The present paper lays the basis of ply-orientation optimization for compliant adaptive wing leading edge in unmanned aerial vehicle（UAV） field.