부산대학교 도서관

The Microwave Imager has emerged as a pivotal payload within meteorological monitoring and assimilation systems, attributed to its comprehensive observational capabilities, which span all weather conditions, daily cycles, and extensive spatial ranges. Nonetheless, the resolution of the channel data from the Microwave Imager is constrained due to limitations inherent in the satellite payload design process. Consequently, this research introduces a remote sensing image restoration algorithm, leveraging Total Variation (TV) regularization deconvolution. Experimental outcomes, derived from both simulated and actual data, reveal that the method offers enhanced image restoration and potent noise suppression. The Peak Signal-to-Noise Ratio (PSNR) of the restored image attains a value of 38.7, while the Structural Similarity (SSIM) achieves a measurement of 0.97.