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Jayanthi Kalikrishnan
L.R. Sudha


Satellite images often have inferior perceptual quality due to environmental and altitude factors of the region it characterizes. Because of insufficient enlightenment the image acquisition system of the satellite captures poor contrast noisy images which need to be processed for better visualization, interpretation and subsequent digital analysis. The discrete wavelet (DWT) coefficients of these images are denoised on the basis of optimal thresholding and shape tuning parameters. The desired thresholding and shape tuning parameters are searched by the nature inspired Ant Lion Optimization (ALO) algorithm in the direction of minimizing the mean squared error risk of the coefficients for better estimation of thresholded DWT coefficients. The illumination information in the denoised thresholded DWT coefficients is uncorrelated by the Singular Value Decomposition (SVD) technique for scaling the intensity of the image. The contrast enhanced image is realized by rebuilding the image using inverse discrete wavelet transformation. The effectiveness of the proposed ALO based methodology has been validated on several low contrast satellite images in terms of visual quality and quantitative performance measures. The superiority of this method is exhibited by comparing the results with state-of-the-art methods.


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