Satellite image processing using discrete cosine transform and singular value decomposition

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Abstract

In this paper, a novel contrast enhancement technique for contrast enhancement of a low-contrast satellite image has been proposed based on the singular value decomposition (SVD) and discrete cosine transform (DCT). The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the SVD-DCT domain and after normalizing the singular value matrix; the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results suggest that the proposed SVD-DCT method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as the histogram equalization, gamma correction and SVD-DWT based techniques. © 2011 Springer-Verlag.

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Ashish, B. K., Kumar, A., & Padhy, P. K. (2011). Satellite image processing using discrete cosine transform and singular value decomposition. In Communications in Computer and Information Science (Vol. 205 CCIS, pp. 277–290). https://doi.org/10.1007/978-3-642-24055-3_29

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