A TRANSFORMATION METHOD FOR TEXTURE FEATURE DESCRIPTION UNDER DIFFERENT IMAGINE CONDITIONS
Keywords: Transformation method, Texture feature, Gabor wavelet, Gaussian mixture models
Abstract. For high spatial resolution Remote Sensing images, it is very important to investigate the transformational methods between background and target characteristics. Only in this way rich details in images under different imaging conditions can be well extracted. Amongst the characteristics of imagery targets, texture is a visual feature that reflects the homogeneity of images and the inner attributes of different objects. What's more, it includes important information which describes the structural arrangement of objects and the connection with the surrounding environment. This paper regards texture as the major feature and investigates the transformational methods of texture feature description under different imaging conditions.
This paper mainly consists of three parts:(1) Construct a wavelet filter based on Gabor wavelet, which describes texture features obtained under different imaging conditions;(2) Process and analyze the different object's texture features jointly by the relationship which is built by the wavelet description;(3) Build the transformation between the wavelet descriptions of the different object's texture features based on the characteristics of the band and direction.