Calligraphy image harmonization algorithm based on local light and shadow perception

The virtual restoration of damaged calligraphy images using image harmonizati on algorithms is of great significance for cultural relic protection. Most existing image harmonization methods focus on addressing the disharmony between foreground and background. In response to the significant visual feature differences and disharmony issues between foreground and background during the virtual restoration of calligraphy images, this paper proposes a calligraphy image harmonization algorithm based on local light and shadow perception on LSPNet. LSPNet precisely locates the area to be restored by introducing reference masks and content masks, thereby ensuring that the style of the synthesized foreground and background remains consistent. To verify the effectiveness of this algorithm, experiments were conducted on damaged calligraphy images. Through numerous experiments and comparisons, LSPNet significantly outperforms other algorithms in reducing the differences in brightness, contrast, and image structure between the foreground and background, making the restored calligraphy works appear more visually natural and unified.