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Graphic design, as a product of the burgeoning new media era, has seen its users' requirements for images continuously evolve. However, external factors such as light and noise often cause graphic design images to become distorted during acquisition. To enhance the definition of these images, this paper introduces a novel image enhancement model based on visual features. Initially, a histogram equalization (HE) algorithm is applied to enhance the graphic design images. Subsequently, image feature extraction is performed using a dual-flow network comprising convolutional neural network (CNN) and Transformer architectures. The CNN employs a residual dense block (RDB) to embed spatial local structure information with varying receptive fields. An improved attention mechanism module, attention feature fusion (AFF), is then introduced to integrate the image features extracted from the dual-flow network. Finally, through image perception quality guided adversarial learning, the model adjusts the initial enhanced image's color and recovers more details. Experimental results demonstrate that the proposed algorithm model achieves enhancement effects exceeding 90% on two large image datasets, which represents a 5%–10% improvement over other models. Furthermore, the algorithm exhibits superior performance in terms of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) image quality evaluation metrics. Our findings indicate that the fusion model significantly enhances image quality, thereby advancing the field of graphic design and showcasing its potential in cultural and creative product design. [ABSTRACT FROM AUTHOR]

Ti-6.5Al-2Zr-1Mo-1V (TA15), widely used in the aerospace industry, is a medium- to high-strength, near-α titanium alloy with high aluminium equivalent value. The TA15 fabricated via laser powder bed fusion (L-PBF) normally presents a typical brittle appearance in as-built status, with high strength and low ductility. In this study, the microstructure and properties of L-PBF TA15 were engineered by various heat treatments below the β-transus temperature (1022 °C). After heat treatment, the original acicular martensite gradually transforms into a typical lamellar α + β dual-phase structure. Withannealing temperature increases, the lamellar α phase thickened with a decreased aspect ratio. Globularisation of the α grain can be noticed when annealing above 800 °C, which leads to a balance between strength and ductility. After heat treatment between 800–900 °C, the desired combination of strength and ductility can be achieved, with elongation of about 12.5% and ultimate tensile strength of about 1100 Mpa. [ABSTRACT FROM AUTHOR]