Pixel-based or texture-based classification technique individually does not yield an appropriate result in classifying the high spatial resolution remote sensing imagery since it comprises textured and non-textured re...Pixel-based or texture-based classification technique individually does not yield an appropriate result in classifying the high spatial resolution remote sensing imagery since it comprises textured and non-textured regions.In this study,Hölder exponents(HE)and variance(VAR)are used together to transform the image for measuring texture.A threshold is derived to segment the transformed image into textured and non-textured regions.Subsequently,the original image is extracted into textured and non-textured regions using this segmented image mask.Afterward,extracted textured region is classified using ISODATA classification algorithm considering HE,VAR,and intensity values of individual pixel of textured region.And extracted non-textured region of the image is classified using ISODATA classification algorithm.In case of non-textured region,HE and VAR value of individual pixel is not considered for classification for significant textural variation is not found among different classes.Consequently,the classified outputs of non-textured and textured regions that are generated independently are merged together to get the final classified image.IKONOS 1 m PAN images are classified using the proposed algorithm,and the classification accuracy is more than 88%.展开更多
In this paper we consider the smoothness of fractal interpolation functions on a general set of nodes, and obtain the estimation of its Hlder exponent.
文摘Pixel-based or texture-based classification technique individually does not yield an appropriate result in classifying the high spatial resolution remote sensing imagery since it comprises textured and non-textured regions.In this study,Hölder exponents(HE)and variance(VAR)are used together to transform the image for measuring texture.A threshold is derived to segment the transformed image into textured and non-textured regions.Subsequently,the original image is extracted into textured and non-textured regions using this segmented image mask.Afterward,extracted textured region is classified using ISODATA classification algorithm considering HE,VAR,and intensity values of individual pixel of textured region.And extracted non-textured region of the image is classified using ISODATA classification algorithm.In case of non-textured region,HE and VAR value of individual pixel is not considered for classification for significant textural variation is not found among different classes.Consequently,the classified outputs of non-textured and textured regions that are generated independently are merged together to get the final classified image.IKONOS 1 m PAN images are classified using the proposed algorithm,and the classification accuracy is more than 88%.
文摘In this paper we consider the smoothness of fractal interpolation functions on a general set of nodes, and obtain the estimation of its Hlder exponent.
