Abstract
Due to high similarity interference of photovoltaic images, repetitive EL image detection and photovoltaic image stitching pose a great challenge. This article proposes two application algorithms and a registration method, which are repetitive EL image detection and photovoltaic image stitching based on the proposed AKAZE-LATCH+GMS registration method. Considering the existence of duplicate EL images acquired indoors, a repetitive EL image detection based on global feature consistency and local cell's texture similarity is proposed. The AKAZE-LATCH+GMS is used to calculate global consistent feature ratio and dHash is used to quantify local cell's similarity to determine whether it is repetitive or not. To solve the problem of high similarity of outdoor photovoltaic images, which leads to dislocation of stitching, an image stitching algorithm based on geographic information is proposed in this article. Compared with AKAZE+GMS and ORB+GMS, the registration experimental results show that the AKAZE-LATCH+GMS method can obtain more initial matching features and higher correct matching rate. Indoor EL images with geometric and illumination differences are used to verify the proposed detection method, which can effectively eliminate repetitive EL images. Aerial photovoltaic images, acquired from the same or different view, are used to verify the validity of the stitching method, and the photovoltaic images can be stitched correctly compared with the stitching method without geographic information.
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