通过构成和相似性评估和改进图像美学质量
Xinyu Cui1, Guoqing Tu2, Guoying Wang2
1College of Software, Quanzhou University of Information Engineering, Quanzhou 362000, China.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
本研究引入了一种新的图像审美评价方法,它协调了构成和相似性,提高了视觉媒体的质量. 拟议的框架优化了图像组成,同时保留了原始内容,在美学吸引力和忠实性方面超过了现有的方法.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 数字媒体艺术 数字媒体艺术
背景情况:
- 图像美学,特别是构成,对于视觉媒体至关重要.
- 现有的优化方法在扭曲,不准确的提取和内容丢失方面扎.
- 需要采用统一的方法来平衡构成美学和图像相似性.
研究的目的:
- 建议使用组合和相似性 (IACS) 方法进行图像美学评估.
- 开发一个框架 (FIACSO) 以优化图像组合,同时保留内容.
- 为了提高优化图像的美学吸引力和真实性.
主要方法:
- 计算语义线/ Salient 对象与组合规则 (三分之一规则,中线) 之间的距离.
- 使用修改后的Hough转换用于语义线检测和LCSF用于突出物体检测.
- 结合Canny边缘检测和SSIM进行相似性评估,用语义细分和GAN进行优化.
主要成果:
- 拟议的IACS方法有效地协调了组合美学和图像相似性.
- FIACSO框架使用语义细分和GAN优化了构成,保留了原始内容.
- 主观评估证实了FIACSO在整体美学,构成和和内容完整性方面的优越性.
结论:
- 开发的方法和框架比现有的图像优化技术提供了显著的改进.
- FIACSO为摄影师和设计师提供实用价值,提高视觉媒体制作效率和质量.
- 这项研究推动了图像美学评估和优化领域的发展.
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