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Background Intensity Estimation for Cassini–ISS Image Using Deep-learning-based Diffusion Model

  • Authors: Yongxin Chen, Qingfeng Zhang, Tianle Zhou, Kai Tang

Yongxin Chen et al 2026 The Astronomical Journal 171 .

  • Provider: AAS Journals

Caption: Figure 4.

Qualitative comparison of background estimation results across three background regimes (ring gap, near ring, and far ring). The rows correspond to the original image and the reconstructions by the traditional method, AOT-GAN, and the proposed DDPM. For each example, the left grayscale panel displays the full 64 × 64 pixel patch, where the central 13 × 13 region represents the estimated background. The right color panel shows the two-dimensional residual map corresponding strictly to the central 13 × 13 masked region, computed as the difference between the predicted and original intensities.

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