https://scholars.lib.ntu.edu.tw/handle/123456789/580651
標題: | 4.7 A 91mW 90fps Super-Resolution Processor for Full HD Images | 作者: | Shen H.-Y Lee Y.-C Tong T.-W CHIA-HSIANG YANG |
關鍵字: | Hash functions; Image enhancement; Object recognition; Optical resolving power; Video streaming; Application scenario; Bicubic interpolation; Extracting features; Hardware accelerators; High resolution image; High-speed applications; Image super resolutions; Neural network (nn); Image reconstruction | 公開日期: | 2021 | 卷: | 64 | 起(迄)頁: | 66-68 | 來源出版物: | Digest of Technical Papers - IEEE International Solid-State Circuits Conference | 摘要: | Super resolution is the process of reconstructing a high-resolution (HR) image from a low-resolution (LR) one. Super-resolution technology enables high-resolution video streaming, image zoom-in, and far object recognition. Fig. 4.7.1 shows such an application scenario. The details of the videos/images can be reconstructed and projected to a higher-resolution screen, thereby providing a better visual experience. A hardware accelerator is needed to speed up the super-resolution process to support real-time high-resolution video streaming. Conventionally, dictionary-based approaches, such as ANR/GR [1] and A+ [2], convert the LR image into the HR one from learned mapping functions. Neural network (NN)-based algorithms generate better-quality super-resolution images by extracting features from training [3]. However, the complexity of the dictionary-based and the NN-based algorithms is excessively high, making them unsuitable for high-speed applications [4]. A rapid and accurate image super resolution (RAISR) algorithm [4] is proposed to achieve comparable quality with a much faster processing speed when compared to the previous solutions. It employs pre-learned filters to enhance the image quality based on bicubic interpolation. A pre-learned filter (also known as kernel) is selected by a hash function to address the structure-related details. ? 2021 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102381476&doi=10.1109%2fISSCC42613.2021.9366026&partnerID=40&md5=d864a78c61358e615e8da0fab0fbb0f2 https://scholars.lib.ntu.edu.tw/handle/123456789/580651 |
ISSN: | 01936530 | DOI: | 10.1109/ISSCC42613.2021.9366026 |
顯示於: | 電機工程學系 |
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