Recognizing low-resolution text images is challenging as they often lose their detailed information, leading to poor recognition accuracy. Moreover, the traditional methods, based on deep convolutional neural networks (CNNs), are not effective enough for some low-resolution text images with dense characters. In this paper, a novel CNN-based batch-transformer network for scene text image super-resolution (BT-STISR) method is proposed to address this problem. In order to obtain the text information for text reconstruction, a pre-trained text prior module is employed to extract text information. ...
