Compression Methods for Satellite Images Using Wavelet Transform and Performance Evaluation

Abstract

Research on image compression spans various fields, focusing on achieving efficient compression while preserving a specific image quality. Satellite images captured by observation satellites, possess unique characteristics distinct from other images. Analyzing these specific traits is crucial, leading to the proposal of tailored compression methods and transforms suitable for satellite image characteristics. This study comprehensively assesses the performance of six well-known compression methods in the literature, utilizing wavelet transform and metrics such as bits per pixel (BPP), compression ratio (CR), Peak Signal-to-Noise Ratio (PSNR), calculation time (CT), and Mean Squared Error (MSE). The compressed satellite images, generated through six methods and the Coif3 wavelet, are systematically compared and evaluated using performance metrics. The average values obtained for all six methods are 96.37%, 47.10 dB, and 7.92 seconds for CR, PSNR and CT receptively, while WDR exhibits CR 96.36%, PSNR 48.84 dB, and CT 6.58 seconds. The findings indicate that the Wavelet Difference Reduction (WDR) compression method utilizing the Coif3 wavelet outperforms others when considering all parameters together. For effective compression of observation satellite images, we suggest that operators and manufacturers choose for wavelet transform and WDR compression methods to achieve optimal results.