Hyperspectral trace gas detection using the wavelet packet transform

A method for trace gas detection in hyperspectral data is demonstrated using the wavelet packet transform. This new method, the Wavelet Packet Subspace (WPS), applies the wavelet packet transform and selects a best basis for pattern matching. The wavelet packet transform is an extension of the wavelet transform, which fully decomposes a signal into a library of wavelet packet bases. Application of the wavelet packet transform to hyperspectral data for the detection of trace gases takes advantage of the ability of the wavelet transform to locate spectral features in both scale and location. By analyzing the wavelet packet tree of specific gas, nodes of the tree are selected which represent an orthogonal best basis. The best basis represents the significant spectral features of that gas. This is then used to identify pixels in the scene using existing matching algorithms such as spectral angle or matched filter. Using data from the Airborne Hyperspectral Imager (AHI), this method is compared to traditional matched filter detection methods. Initial results demonstrate a promising wavelet packet subspace technique for hyperspectral trace gas detection applications.

[1]  James Theiler,et al.  Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[2]  David A. Landgrebe,et al.  Some fundamentals and methods for hyperspectral image data analysis , 1999, Photonics West - Biomedical Optics.

[3]  S. Twomey.  Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements , 1997 .

[4]  Roger L. King,et al.  Hyperspectral data analysis using wavelet-based classifiers , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[5]  M. Lennon,et al.  Spectral unmixing of hyperspectral images with the independent component analysis and wavelet packets , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[6]  John A. Richards,et al.  Remote Sensing Digital Image Analysis: An Introduction , 1999 .

[7]  Jiang Li,et al.  Automated detection of subpixel hyperspectral targets with adaptive multichannel discrete wavelet transform , 2002, IEEE Trans. Geosci. Remote. Sens..

[8]  John R. Schott,et al.  Remote Sensing: The Image Chain Approach , 1996 .

[9]  Yi-Hsing Tseng,et al.  Feature extraction of hyperspectral data using the Best Wavelet Packet Basis , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[10]  Jun Zheng,et al.  Wavelet based feature reduction method for effective classification of hyperspectral data , 2003, Proceedings ITCC 2003. International Conference on Information Technology: Coding and Computing.

[11]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[12]  Richard C. Olsen,et al.  LWIR spectral measurements of volcanic sulfur dioxide plumes , 2004, SPIE Defense + Commercial Sensing.

[13]  S. W. Sharpe,et al.  The PNNL quantitative IR database for infrared remote sensing and hyperspectral imaging , 2002, Applied Imagery Pattern Recognition Workshop, 2002. Proceedings..

[14]  N. S. Subotic,et al.  Robust material identification in hyperspectral data via multiresolution wavelet techniques , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[15]  A. Berk,et al.  FLAASH and MODTRAN4: state-of-the-art atmospheric correction for hyperspectral data , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).

[16]  Michael T. Heath,et al.  Scientific Computing: An Introductory Survey , 1996 .

[17]  Paul G. Lucey,et al.  Detection and identification of toxic air pollutants using airborne LWIR hyperspectral imaging , 2005, SPIE Asia-Pacific Remote Sensing.

[18]  Truong Q. Nguyen,et al.  Wavelets and filter banks , 1996 .

[19]  D. Walnut.  An Introduction to Wavelet Analysis , 2004 .