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A Systematic Approach to Wavelet-Decomposition-Level Selection for Image Information Mining From Geospatial Data Archives

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4 Author(s)
Shah, V.P. ; Dept. of Electr. & Comput. Eng., Mississippi State Univ., MS ; Younan, N.H. ; Durbha, S.S. ; King, R.L.

Recently, wavelet-based methods have been efficiently used for segmentation and primitive feature extraction to expedite the image-retrieval process of semantic-enabled frameworks for image information mining from geospatial data archives. However, the use of wavelets may introduce aliasing effects due to subband decimation at a certain decomposition level. This paper addresses the issue of selecting a suitable wavelet decomposition level, and a systematic selection process is developed. To validate the applicability of this method, a synthetic image is generated to qualitatively and quantitatively assess the performance. In addition, results for a Landsat-7 Enhanced Thematic Mapper Plus imagery archive are illustrated, and the F-measure is used to assess the feasibility of this method for the retrieval of different classes

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:45 ,  Issue: 4 )

Date of Publication:

April 2007

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