Urban Image Segmentation in Media Integration Era Based on Improved Sparse Matrix Generation of Digital Image Processing

Media integration integrates the resources of various media platforms, including audience, technical and human resources. In the era of media integration, media in various channels, at different levels and in different fields provide various choices for image communication and brand building of cities. The technology of image processing by computer has gradually affected all aspects of people’s life and work, bringing more and more convenience to people. In this paper, the application of digital image processing technology in city image communication in the age of media integration is studied. A new sparse matrix creation method is proposed, and the created sparse matrix is used as the similarity matrix to segment the spectral clustering image, so that the edge contour weakened in gradient calculation can be corrected and strengthened again. The research shows that the improved algorithm is superior to the traditional algorithm, and compared with the fuzzy entropy algorithm based on exhaustive search, the gray contrast between regions and Bezdek partition coefficient are improved by 9.301% and 4.127%. In terms of speed, the algorithm in this paper has absolute advantages, so our research is also affirmed, which fully shows that it should have high application value.

@article{Zheng2023,
  title     = {Urban Image Segmentation in Media Integration Era Based on Improved Sparse Matrix Generation of Digital Image Processing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {12},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Dan Zheng and Yan Xie},
  doi       = {10.14569/IJACSA.2023.0141235},
  url       = {https://doi.org/10.14569/IJACSA.2023.0141235}
}