Design of a residual block that provides a rich set of features while requiring only small numbers of parameters and operations is crucial for the task of single image super resolution. This is especially important in applications with limited power and storage capacity. In this paper, a new multi-domain residual block is proposed in order to generate richer set of features for the task of image super resolution. The proposed residual block consists of two feature generation modules. The first one is a spatial information processing module and the second one is a spectral information processing module. The feature maps obtained by these two feature generation modules are concatenatively fused to obtain block's output. The new residual block is used to build light-weight super resolution networks. Extensive experiments are performed using several benchmark datasets in order to evaluate the performance of the networks using the new multi-domain residual block. It is shown that the use of both the spatial and spectral features enhances the performance of the light-weight super resolution networks.

中文翻译：

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SRNSSI：使用空间和光谱信息实现单图像超分辨率的深轻网络

残差块的设计可提供丰富的功能，而仅需少量参数和操作，对于单图像超分辨率的任务至关重要。这在功率和存储容量有限的应用中尤其重要。本文提出了一种新的多域残差块，以便为图像超分辨率任务生成更丰富的特征集。提议的残差块由两个特征生成模块组成。第一个是空间信息处理模块，第二个是光谱信息处理模块。这两个特征生成模块获得的特征图被串联融合以获得块的输出。新的残差块用于构建轻型超分辨率网络。使用几个基准数据集进行了广泛的实验，以便使用新的多域残差块评估网络的性能。结果表明，空间和光谱特征的使用都增强了轻型超分辨率网络的性能。