Abstract: Image super-resolution (SR) aims to enhance the spatial resolution of images and overcome the hardware limitations of imaging systems. While deep-learning networks have significantly ...
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Our code is runned on the Pytorch framework with the following environment configurations. CUDA 11.7 Python 3.9.19 PyTorch 1.13.1 + cu117 mamba_ssm 1.0.1 Following most previous lightweight SR methods ...
Table 1. Computational comparison of SR architectures. Additionally, computational overhead remains prohibitive for edge deployment. Existing efficient methods (Wang et al., 2024) require L sequential ...
Abstract: Recent advancements in tensor nuclear norm (TNN) have led to promising solutions for hyperspectral image super-resolution (HSISR), which produces enriched outputs by fusing low-resolution ...