Fuzzification of a Crisp Near-Real-Time Operational Automatic Spectral-Rule-Based Decision-Tree Preliminary Classifier of Multisource Multispectral Remotely Sensed Images

摘要

Proposed in recent literature, a novel two-stage stratified hierarchical hybrid remote-sensing image understanding system (RS-IUS) architecture comprises the following: 1) a first-stage pixel-based application-independent top-down (physical-model-driven and prior-knowledge-based) preliminary classifier and 2) a second-stage battery of stratified hierarchical context-sensitive application-dependent modules for class-specific feature extraction and classification. The first-stage preliminary classifier is implemented as an operational automatic near-real-time per-pixel multisource multiresolution application-independent spectral-rule-based decision-tree classifier (SRC). To the best of the author''s knowledge, SRC provides the first operational example of an automatic multisensor multiresolution Earth-observation (EO) system of systems envisaged under ongoing international research programs such as the Global Earth Observation System of Systems (GEOSS) and the Global Monitoring for the Environment and Security (GMES). For the sake of simplicity, the original SRC formulation adopts crisp (hard) membership functions unsuitable for dealing with component cover classes of mixed pixels (class mixture). In this paper, the crisp (hierarchical) SRC first stage of a two-stage hybrid RS-IUS is replaced by a fuzzy (horizontal) SRC. In operational terms, a relative comparison of the fuzzy SRC against its crisp counterpart reveals that the former features the following: 1) the same degree of automation which cannot be surpassed, i.e., they are both ȁC;fully automaticȁD;; 2) a superior map information/knowledge representation where component cover classes of mixed pixels are modeled; 3) the same robustness to changes in the input multispectral imagery acquired across time, space, and sensors; 4) a superior maintainability/scalability/reusability guaranteed by an internal horizontal (flat) modular structure independent of hierarchy; and 5) a computation time increased -n-nby 30% in a single-process single-thread implementation. This computation overload would reduce to zero in a single-process multithread implementation. In line with theory, the conclusion of this work is that the operational qualities of the fuzzy and crisp SRCs differ, but both SRCs are suitable for the development of operational automatic near-real-time multisensor satellite-based measurement systems such as those conceived as a visionary goal by the ongoing GEOSS and GMES research initiatives.