Haze Removal from the Visible Bands of CBERS Remote Sensing Data

Remote sensing images can widely used in many scientific research fields for its ability of detecting large area simultaneously and quickly. However, persistent cloud and haze region effect on their use. This paper used haze optimized transformation (HOT) transformation to remove haze region from CBERS remote sensing data. Band 1 and band 3 of CBERS image are selected to generate HOT image using linear regression, then HOT image was applied for the image to remove the radiometric effects of the haze. Comparing the result before and after haze removal, the image after processed is clearer than before. HOT transformation is a robust haze removal algorithm. It is also suitable for CBERS remote sensing data. Haze removal can improve evaluation of remote sensing data, especially for multi-spectral images.

[1]  J. Cihlar,et al.  An image transform to characterize and compensate for spatial variations in thin cloud contamination of Landsat images , 2002 .

[2]  Freek D. van der Meer,et al.  Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain , 2008 .

[3]  Xiaofeng Yang,et al.  CBERS-02 Remote Sensing Data Mining Using Decision Tree Algorithm , 2008, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008).

[4]  H. Loisel,et al.  Variability and classification of remote sensing reflectance spectra in the eastern English Channel and southern North Sea , 2007 .

[5]  Xiaofeng Yang,et al.  An Investigation of the Relationship between Land Cover Ratio and Urban Heat Island , 2008, 2008 Congress on Image and Signal Processing.

[6]  B. Guindon,et al.  ROBUST HAZE REDUCTION: AN INTEGRAL PROCESSING COMPONENT IN SATELLITE-BASED LAND COVER MAPPING , 2002 .

[7]  E. Ben-Dor,et al.  Quantitative mapping of arid alluvial fan surfaces using field spectrometer and hyperspectral remote sensing , 2006 .

[8]  Xiaofeng Yang,et al.  An Operational Improvement of Haze/Clear Line Identification from Satellite Imagery Based on Multi-Resolution Segmentation , 2008, 2008 Second International Symposium on Intelligent Information Technology Application.

[9]  Rudolf Richter,et al.  Atmospheric correction of satellite data with haze removal including a haze/clear transition region , 1996 .

[10]  Yong Du,et al.  Haze detection and removal in high resolution satellite image with wavelet analysis , 2002, IEEE Trans. Geosci. Remote. Sens..

[11]  Raymond F. Kokaly,et al.  Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing , 2007 .

[12]  C. Ji,et al.  Haze reduction from the visible bands of LANDSAT TM and ETM+ images over a shallow water reef environment , 2008 .

[13]  Lena Halounová,et al.  Haze removal for high‐resolution satellite data: a case study , 2007 .

[14]  Philip Lewis,et al.  Canopy spectral invariants for remote sensing and model applications , 2007 .