RGBD Synergetic Model for Image Enhancement in Animation Advertisements

Abstract

This paper proposes a depth image symbiosis model to solve the problem of insufficient depth image quality in animated advertising. The model uses image surface information and image edge cues as the main guidance information to obtain image symbiosis information. Research data show that the model designed in this paper performs well in convergence, and enters a stable convergence process when the number of iterations is less than 5. Its PSNR data curve has the highest position and best performance, while a composite model structure has been adopted. Compared with the unitary model, the PSNR of this model reaches 41 dB when the number of iterations reaches 5, and the convergence effect of the three-step training is also better. Finally, in practical applications, the average PSNR value of the model mentioned in this article is the highest, 37.1 dB. From this comprehensive perspective, the depth image enhancement model in this study has better comprehensive performance and can provide better image enhancement effects for animation advertising depth images.