Single image super-resolution (SISR) is an intensively studied topic in image processing. It aims at recovering a high-resolution (HR) image from its low-resolution (LR) counterpart. SISR finds wide real-world applications such as remote sensing, medical imaging, and biometric identification. Besides, it attracts attention due to its connection with other tasks (e.g., image registration, compression, and synthesis).
The main challenge of SISR is the ill-pose issue. We recently have been developing a solution by providing reasonable performance and effectively reduced complexity. We propose a green U-shape method to progressively enhance the LR images from global structure to local details with increasing spatial sizes and conditional residual estimation.
