Image Processing Techniques for Satellite Terrain Analysis

Sami, Kanar; Alkawaz, Esraa

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Proceedings of International Conference on Applied Innovation in IT · 2026/06/12 · Vol. 14 · Issue 3 · pp. 215–223

Image Processing Techniques for Satellite Terrain Analysis

Kanar Sami, Esraa Abd Alsalam and Mohammed Hazim Alkawaz

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Abstract

The contourlet transform had been used in the multimedia processing works and processes of compression, encoding, and steganography of audio and with images and video data. In the present study, satellite images recorded with the Sentinel-2 were used to investigate the drainage systems in the Mosul Dam Basin. The high-frequency coefficients were removed selectively and reconstructed with the remaining coefficients to analyse how frequency loss affect the quality of images. The contribution of low-frequency components to reconstructed images was further determined in numerical terms measured by mean squared error and the Signal to noise ratio, normalized root mean square deviation (NRM), and correlation coefficient. Across some decomposition levels, results from experiments on bands 1, 2 and 4 demonstrated that low NRM values, high SNR values, and correlation coefficients converged into unity, suggesting a reasonable estimation accuracy. The cut off values for frequency elimination were taken using standard deviation (STD) and median absolute deviation (MAD) criteria. The data supported the effectiveness of the contourlet-based frequency assessment which evaluated the influence of removing coefficients on satellite image characteristics for the following scenarios: data compression, edge detection, noise removal, and terrain feature extraction for drainage pattern maps in the Mosul Dam region.

Keywords

Mean Absolute Deviation Satellite Data Contourlet Transform Digital Image Processing Standard Deviation.

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