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Pan-Sharpening Using an Efficient Bidirectional Pyramid Network

机译：使用高效的双向金字塔网络进行平移锐化

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摘要

Pan-sharpening is an important preprocessing step for remote sensing image processing tasks; it fuses a lowresolution multispectral image and a high-resolution (HR) panchromatic (PAN) image to reconstruct a HR multispectral (MS) image. This paper introduces a new end-to-end bidirectional pyramid network for pan-sharpening. The overall structure of the proposed network is a bidirectional pyramid, which permits the network to process MS and PAN images in two separate branches level by level. At each level of the network, spatial details extracted from the PAN image are injected into the upsampled MS image to reconstruct the pan-sharpened image from coarse resolution to fine resolution. Subpixel convolutional layers and the enhanced residual blocks are used to make the network efficient. Comparison of the results obtained with our proposed method and the results using other widely used state-of- the-art approaches confirms that our proposed method outperforms the others in visual appearance and objective indexes.
机译：锐化锐化是遥感图像处理任务的重要预处理步骤；它融合了低分辨率多光谱图像和高分辨率（HR）全色（PAN）图像，以重建HR多光谱（MS）图像。本文介绍了一种用于泛锐化的新的端到端双向金字塔网络。所提出的网络的整体结构是双向金字塔，它允许网络逐级处理两个单独分支中的MS和PAN​​图像。在网络的每个级别，将从PAN图像提取的空间细节注入到上采样的MS图像中，以将泛锐化后的图像从粗分辨率重建为高分辨率。亚像素卷积层和增强的残差块用于提高网络效率。使用我们提出的方法获得的结果与使用其他广泛使用的最新方法得出的结果进行比较，证实了我们提出的方法在视觉外观和客观指标上均优于其他方法。

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