TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatiooral Single Image Super Resolution

Fayaz Ali Dharejo, Farah Deeba, Yuanchun Zhou, Bhagwan Das, Munsif Ali Jatoi, Muhammad Zawish, Yi Du, Xuezhi Wang

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Single Image Super-resolution (SISR) produces high-resolution images with fine spatial resolutions from a remotely sensed image with low spatial resolution. Recently, deep learning and generative adversarial networks (GANs) have made breakthroughs for the challenging task of single image super-resolution (SISR). However, the generated image still suffers from undesirable artifacts such as the absence of texture-feature representation and high-frequency information. We propose a frequency domain-based spatiooral remote sensing single image super-resolution technique to reconstruct the HR image combined with generative adversarial networks (GANs) on various frequency bands (TWIST-GAN). We have introduced a new method incorporating Wavelet Transform (WT) characteristics and transferred generative adversarial network. The LR image has been split into various frequency bands by using the WT, whereas the transfer generative adversarial network predicts high-frequency components via a proposed architecture. Finally, the inverse transfer of wavelets produces a reconstructed image with super-resolution. The model is first trained on an external DIV2 K dataset and validated with the UC Merced Landsat remote sensing dataset and Set14 with each image size of 256 × 256. Following that, transferred GANs are used to process spatiooral remote sensing images in order to minimize computation cost differences and improve texture information. The findings are compared qualitatively and qualitatively with the current state-of-art approaches. In addition, we saved about 43% of the GPU memory during training and accelerated the execution of our simplified version by eliminating batch normalization layers.

Original languageBritish English
Article number71
JournalACM Transactions on Intelligent Systems and Technology
Issue number6
StatePublished - Dec 2021


  • neural networks
  • spatiooral
  • super resolution
  • Wavelet transform


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