Abstract
This paper presents a fuzzy estimation method for the class mixture proportion of the mixed pixel (mixel) on a remote sensing image. The training data were selected by the operator based on the subjectivity and its distribution was defined as a fuzzy set on a spectral space. It was also assumed that the spectral characteristics of the mixel was regarded as a linear function of the reflection levels of the pure pixels corresponding to the component classes. A fuzzy production rule for the estimation of the class mixture proportion on the mixel was defined in accordance with this assumption. The estimation of the class mixture proportion for the proposed method was conducted by the fuzzy simplification reasoning method.
It was observed that the estimation accuracy of the fuzzy estimation method depended on the mesh interval. The mesh interval means the change percentage of the class mixture rate for the formation of the membership function. That is, the Total Root Mean Square error (TRMS) of the estimated value tended to decrease when reducing the mesh interval. The simulation results also indicated that the reasonable mesh interval (the change percentage of the class mixture rate) of the membership function might be about 0.05 (5%). It was also observed that the proposed method gave low TRMS to the simulation data which was produced by the random sampling of the training data of each class. Therefore, it was confirmed that the proposed fuzzy estimation method was an useful technique to estimate the class mixture proportion of the mixel on an actual remote sensing image.
