Abstract
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.
Highlights
As a natural attribute of subjects, texture is a visual feature that reflects the homogeneity of images
As few people are working on researching the transformational methods of texture features description under different imaging conditions so far, few papers can be found in this area
The registered local texture of QuickBird imagery and synthetic aperture radar (SAR) imagery used in this experiment are shown in figure7 and figure8
Summary
As a natural attribute of subjects, texture is a visual feature that reflects the homogeneity of images. All of the above methods of texture features description under different imaging conditions can be divided into five categories according to the principle proposed (Tuceryan, Jain, 1993) They are statistical methods, geometrical methods, structural methods, model based methods and signal processing methods. This paper will research the investigating transformational methods of texture features description under different imaging conditions based on Gabor wavelet. As few people are working on researching the transformational methods of texture features description under different imaging conditions so far, few papers can be found in this area. This will be the main research content of our paper.
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