Image quality assessment model based on multi-feature fusion of energy Internet of Things

Abstract Image information may be distorted during acquisition, propagation, compression, and storage. Distortion is common in real life, but it affects the subjective experience after acquiring an image. In order to improve the subjective experience, it is necessary to properly evaluate the image quality. This paper discusses image quality assessment without reference. This paper proposes a new method for image quality assessment. In complex scenarios, we deploy multiple critical sensors. We use sensors to get the necessary factors in the environment. After acquiring the feature values, we fuse the acquired information. We propose a multi-feature fusion method based on the Internet of Things to evaluate images. After the information is merged, we get a fused image and use it as a reference image. We converted the no-reference image assessment into a full reference image assessment, and applied the corresponding image assessment method to obtain the corresponding assessment results. In the process of experimental verification, we compare the prediction results with the subjective assessment of the human eye. It can be seen that our method is close to subjective judgment.