Semantic Segmentation on Multi-Spectral Images

Semantic segmentation is considered to be one of the basic steps in understanding image content. For semantic segmentation, if multi-spectral images are used together with color images, more successful results are obtained due to complementary information obtained from multi-spectral images. In this paper, a semantic segmentation method was developed in which the images obtained from CCD and thermal sensors were used together. In the proposed method, convolutional neural networks were used in encoder-decoder architecture. The experiments carried out show that the developed method produces better numerical and visual results than the works published in the literature.