Mutiple-Image SSR 关键的技术imformation fusion 1. 将单一场景的多图像经过Resnet, 其中每张图片的维度变为了输入的两倍。同时,这些输入的单一场景的多图像进行图像配准(image registration)来确定图像之间的 子像素的位移(位移值乘以2以适配于Resnet的输出) 2. 经过Resnet的结果与子像素移位一起使用中值移位和加法...
Multiple-image super-resolution (MISR) attempts to recover a high-resolution (HR) image from a set of lowresolution (LR) images. In this paper, we present a mobile MISR tailored to work for a wide range of mobile devices. Our technique aims to address misalignment issues from a previous ...
The Image Super-Resolution converts standard definition to vivid high definition image better than conventional up-scaler. The Multiple Video Playback decodes and displays 48 video streams on the screen with optimized program.关键词: Multiple Video Playback Cell Processor Image Super-Resolution ...
Single image super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) images. Existing SR algorithms often lose information when dealing with complex textures and details, and the model's feature weighting in different regions is unreasonable, leading ...
Recent research efforts have focused on combining high dynamic range (HDR) imaging with super-resolution (SR) reconstruction to enhance both the intensity range and resolution of images beyond the apparent limits of the sensors that capture them. The processes developed to date start with a set of...
Single image super-resolution (SISR) aims to recover clear high-resolution images from low-resolution images, which has made great progress with the development of deep learning these years. Scene text image super-resolution (STISR) is a subfield of SISR with the goal of increasing the resolutio...
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented ...
convolutional network for image super-resolution. In European Conference on Computer Vision, pages 184–199, 2014. 2 [9] C. Dong, C. C. Loy, K. He, and X. Tang. Image super-resolution usingdeep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, ...
Super resolution allows us to reduce the need of extra hardware to obtain HR image. This paper proposes a new method for super resolution video generation with sharpened edges using multiple frames. Unique information present in subpixel shifted frames is extracted and used for frequency domain ...
Example learning-based superresolution (SR) algorithms show promise for restoring a high-resolution (HR) image from a single low-resolution (LR) input. The most popular approaches, however, are either time- or space-intensive, which limits their practical applications in many resource-limited setti...