Creative and high-quality image composition based on a new criterion

Wavelet pyramids and features handling were used to achieve high-quality and multi-scale compositions.One new criterion was utilized to ensure the composite results were semantically valid. Image compositing techniques are primarily utilized to achieve realistic composite results. Some existing image compositing methods, such as gradient domain and alpha matting, are widely used in the field of computer vision, and can typically achieve realistic results, especially for seamless boundaries. However, when the candidate composite images and the target images have obvious differences, such as color, texture and brightness, the composite results are unrealistic and inconsistent. At the same time, traditional compositing methods focus on basic feature matching, ignoring semantic rationality in composition processing. Quite a few compositing methods thus generate composite results without semantic rationality.In this paper, a new multi-scale image composition method has been presented. In the composition process, wavelet pyramid and basic feature handling were used to achieve multi-scale compositions. More importantly, a new criterion was established, based on the semantic rationality of images, which could ensure that the composite images are semantically valid. A large database was created to facilitate experimentation. The experiments showed that the methodology introduced in this paper produced superior results compared to traditional composition methods; the composite results were not only consistent and seamless, but were also semantically valid.