Feature-Oriented Artistic Styles Transfer Based on Effective Texture Synthesis

The research of image visual characteristics transfer is motivated from texture synthesis techniques. Generally, the success of these applications is inherently useroriented and highly depends on the subjective personal thoughts also. Therefore, a method with the reasonable estimation values to synthesize a styled texture which would meet the user preference is highly desirable. In this paper, the algorithm starts with an activityguided analysis for adaptive patch-based visual characteristics transfer, which is not only more efficient than conventional methods but also with pleasing visual quality. Then, the Particle Swarm Optimization (PSO) accelerated scheme with a modified match criterion which can effectively search and the approximate best location that matches the synthesized target patch according to user-specified feature(s). In addition, a hybrid blending approach ensures the Coherence Match to improve the transition effect between the overlapping boundaries of adjacent patches is proposed. The experimental results demonstrate that our method provides greater flexibility and better performance of perceptual visualization for the applications of artistic styles transfer.