Wavelet Enhancement of Cloud-related Shadow Areas in Single Landsat Satellite Imagery

Cloud-related shadows represent areas with low illumination conditions that affect remote sensing image quality. In this research, a wavelet-based image sharpening algorithm was developed to enhance shadow areas independently using the defected cloudy image information. The developed algorithm is applied locally by boosting the image high frequency content in the shadow areas using the defected image de-noised wavelet coefficients. Image entropy was used as a measure to determine the change in wavelet coefficient values. The developed algorithm was tested on the panchromatic band of a November 2001 Landsat 7 ETM satellite subscenes. Another cloud-free image was used as reference image for results evaluation and quality analysis. Several discrete wavelet decomposition levels were tested. Quantitative measures were used to evaluate the obtained results. Visual and quantitative analysis of the results revealed that the ability to enhance details under shadow areas increased with the increase in the number of wavelet decomposition levels. Two or three wavelet decomposition levels were found to be sufficient for enhancing image quality in the shadow areas while avoiding introduced artifacts. Conclusions and recommendations are given with respect to the suitability, accuracy and efficiency of this method.