International Journal of Remote Sensing · 2014 · 59 citations · 37 references
ArtsGeoinformaticsComputer VisionDigital ImagingRemote SensingDigital Image ProcessingDigital Signal ProcessingImage EnhancementImage ProcessingImage QualityRemote Sensing Image AnalysisArtificial Bee ColonyContrast EnhancementContrast Enhancement AlgorithmsDiscrete Wavelet TransformHistogram EqualizationSingular Value DecompositionThresholdingWavelet Transform
In this article, a new contrast enhancement approach is presented for quality enhancement of low-contrast satellite images. The proposed technique is based on the Artificial Bee Colony (ABC) algorithm using Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). The method employs the ABC technique to learn the parameters of the adaptive thresholding function required for optimum enhancement. In this approach, the input image is primarily decomposed into four sub-bands through DWT, and then each sub-band of DWT is optimized through the ABC algorithm. After that, a singular value matrix of the low–low thresholded sub-band image is estimated and, finally, the enhanced image is constructed by applying inverse DWT. The results obtained through this method reveal that the proposed methodology gives better performance in terms of peak signal-to-noise ratio (PSNR), mean square error (MSE), and mean and standard deviation as compared to General Histogram Equalization (GHE), Discrete Cosine Transfor...
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