Image quality enhancement algorithm based on game theory model

Image quality enhancement algorithm based on game theory model is designed in this research. The core idea of the algorithm is to enumerate the sequence of sub-pictures obtained from different free parameters, and then perform image fusion according to the image details, saturation, and brightness, and then fuse a higher quality enhanced image. At present, with the development of image processing technology, feature extraction and matching algorithm will be an important research direction in the field of intelligent data. This research work integrates the game theory model to construct the efficient image analytics model. The experiment results are compared with the latest methods to evaluate the proposed framework from the robustness and accuracy perspective.