Introductory Digital Image Processing: A Remote Sensing Perspective
Introductory Digital Image Processing: A Remote Sensing Perspective
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Generalized Additive Models (Texts in Statistical Science)
Generalized Additive Models (Texts in Statistical Science)
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
A survey of image classification methods and techniques for improving classification performance
International Journal of Remote Sensing
SVM-based segmentation and classification of remotely sensed data
International Journal of Remote Sensing
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
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This Letter proposes an object-based image classification procedure which is based on fuzzy image-regions instead of crisp image-objects. The approach has three stages: (a) fuzzification in which fuzzy image-regions are developed, resulting in a set of images whose digital values express the degree of membership of each pixel to target land-cover classes; (b) feature analysis in which contextual properties of fuzzy image-regions are quantified; and (c) defuzzification in which fuzzy image-regions are allocated to target land-cover classes. The proposed procedure is implemented using automated statistical techniques that require very little user interaction. The results indicate that fuzzy segmentation-based methods produce acceptable thematic accuracy and could represent a viable alternative to current crisp image segmentation approaches.