대한원격탐사학회:학술대회논문집 (Proceedings of the KSRS Conference)
- 대한원격탐사학회 2008년도 춘계학술대회 논문집
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- Pages.195-200
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- 2008
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- 1226-9743(pISSN)
Statistical Approach to Noisy Band Removal for Enhancement of HIRIS Image Classification
- Huan, Nguyen Van (Image Information Research Center School of Information and Communication Engineering, INHA University) ;
- Kim, Hak-Il (Image Information Research Center School of Information and Communication Engineering, INHA University)
- 발행 : 2008.03.21
초록
The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.