The transformation and innovation of regional art characteristic elements in digital media art are faced with some problems, such as difficult technical realization, insufficient cultural expression, and imperfect copyright protection. It is urgent to promote its effective transformation and innovative application through advanced digital technology. Especially with the application of cutting-edge technologies such as generative adversarial networks (GAN) and blockchain, the digital expression and innovation of regional art elements have taken a new direction. Firstly, this paper systematically analyzes the definition of regional art characteristic elements and their expression forms in digital art, focusing on the extraction methods of texture, color, and composition and their technical realization. Through digital storage and management technology, the efficient storage and rapid query of regional art elements are ensured, and its application value in digital media art is further enhanced through parametric modeling and visual presentation. This paper introduces an artistic element generation method based on a generative adversarial network (GAN). The query response time averages 21% in all experiments, which is fast and effective. In the data integrity test, the integrity retention rate of images reaches 38.2%, which shows that the storage system can keep the original characteristics of regional art elements well. Blockchain technology is outstanding in copyright protection. The transaction delay of artistic works is 76 milliseconds, and the data security guarantee rate is as high as 55.6%. Regarding the evaluation of generated images, the emotional expressiveness of the generative adversarial network (GAN) model used in the experiment when generating artworks IS 48%, and the image quality IS high, with an FID of 19.3 and IS score of 84.7, which further verifies the application effect of digital technology in regional art innovation.