Motivated by human behavior, dividing inpainting tasks into structure reconstruction and texture generation helps to simplify restoration process and avoid distorted structures and blurry textures. However, most of tasks are ineffective for dealing with large continuous holes. In this paper, we devise a parallel adaptive guidance network(PAGN), which repairs structures and enriches textures through parallel branches, and several intermediate-level representations in different branches guide each other via the vertical skip connection and the guidance filter, ensuring that each branch only leverages the desirable features of another and outputs high-quality contents. Considering that the larger the missing regions are, less information is available. We promote the joint-contextual attention mechanism(Joint-CAM), which explores the connection between unknown and known patches by measuring their similarity at the same scale and at different scales, to utilize the existing messages fully. Since strong feature representation is essential for generating visually realistic and semantically reasonable contents in the missing regions, we further design attention-based multiscale perceptual res2blcok(AMPR) in the bottleneck that extracts features of various sizes at granular levels and obtains relatively precise object locations. Experiments on the public datasets CelebA-HQ, Places2, and Paris show that our proposed model is superior to state-of-the-art models, especially for filling large holes.

In global skin-friction measurement of aircraft, the fluorescent oil film method can characterize the distribution of skin friction well. However, in an actual wind tunnel test, the wing of the aircraft will inevitably produce corresponding vibrations due to the influence of wind, which will change the relative position between fluorescent oil film and UV (ultraviolet) excitation light source (position fixed). This also directly affects gray value imaging of fluorescent oil films. Based on this, a mathematical model is established to judge the stability of the gray value of fluorescent oil film in this vibrational environment; then, the model can be solved to obtain the vibrational range constraint that enables the gray value of fluorescent oil film to be stabilized. In order to simplify the calculation process, the light vector angle is used to describe the constraint, which also makes the results more intuitive. Through experimental analysis and demonstration, the prediction accuracy of this model can reach 95.61%, which has certain practical engineering application significance.