[1] DONG C, LOY C C, HE K M et al. Image super-resolution using deep convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2016).

[2] KIM H et al. Enhanced deep residual networks for single image super-resolution[C], 1132-1140(2017).

[3] ZHANG Y L, TIAN Y P, KONG Y et al. Residual dense network for image super-resolution[C], 2472-2481(2018).

[4] HUI Z, WANG X M, GAO X B. Fast and accurate single image super-resolution via information distillation network[C], 723-731(2018).

[5] LIANG J Y, CAO J Z, SUN G L et al. SwinIR： image restoration using swin transformer[C], 1833-1844(2021).

[6] ZAMIR S W, ARORA A, KHAN S et al. Restormer： efficient transformer for high-resolution image restoration[C], 5718-5729(2022).

[7] WANG H, CHEN X H, NI B B et al. Omni aggregation networks for lightweight image super-resolution[C], 22378-22387(2023).

[8] CHEN Z, ZHANG Y L, GU J J et al. Dual aggregation transformer for image super-resolution[C], 12278-12287(2023).

[9] YU W H, ZHOU P, YAN S C et al. InceptionNeXt： when inception meets ConvNeXt[C], 5672-5683(2024).

[10] DONG C, LOY C C, TANG X O. Accelerating the super-resolution convolutional neural network[C], 391-407(2016).

[11] KANG B, SOHN K A[M]. Fast， Accurate， and Lightweight Super-Resolution with Cascading Residual Network, 256-272(2018).

[12] CHOI H, LEE J, YANG J. N-gram in swin transformers for efficient lightweight image super-resolution[C], 2071-2081(2023).

[13] LI A, ZHANG L, LIU Y et al. Feature modulation transformer： cross-refinement of global representation Via high-frequency prior for image super-resolution[C], 12480-12490(2023).

[14] GUO H, LI J M, DAI T et al[M]. MambaIR： A Simple Baseline for Image Restoration with State-Space Model, 222-241(2024).

[15] LI F, CONG R M, WU J J et al. SRConvNet： a transformer-style ConvNet for lightweight image super-resolution[J]. International Journal of Computer Vision, 133, 173-189(2025).

[16] ZHANG X, ZHANG Y L, YU F[M]. HiT-SR： Hierarchical Transformer for Efficient Image Super-Resolution, 483-500(2024).