Ning Liu
ABSTRACT
The quality correction of transmission line images is of great significance for power system monitoring and maintenance. The purpose of this study is to propose an automatic quality correction algorithm based on saliency model to improve the clarity and visibility of transmission line images. We combine modern computer vision technology with saliency analysis, and propose an innovative method, which can automatically detect and correct the quality problems in transmission line images. In this paper, an automatic quality correction algorithm for transmission line images based on the salient deep features of pseudo-reference images is proposed. The algorithm mainly consists of three parts, namely, pseudo reference image generation network, deep feature extraction network and quality regression network. The experimental results show that the quality prediction of this algorithm accords with human quality perception, and the prediction score is in good agreement with human subjective quality evaluation. The algorithm can automatically detect the salient regions in the image and adjust the correction parameters according to the characteristics of these regions. This adaptability enables our algorithm to process transmission line images under different lighting conditions, thus improving its universality. The successful application of this algorithm will hopefully improve the operation and maintenance of the power system, thus achieving a more sustainable power supply.
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Index Terms
- Automatic Quality Correction Algorithm Design for Transmission Line Images Based on the Saliency Model
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