{"title":"基于FPGA的牙科x射线自适应实时增强系统","authors":"Haoyang Sang, Junsong Zhang, Liyi Yao, Zhao Wang, Kunmeng Luo, Wumeng Yin, Meng You, Bo Gao","doi":"10.1109/ICECE54449.2021.9674312","DOIUrl":null,"url":null,"abstract":"Dental X-ray imaging which shows the clear internal structure of teeth is essential for diagnosis. However, the image details in both dark and bright regions are often hard to distinguish due to the misoperation and the limitation of dental Xray imaging machines. In addition, the emergence of some realtime X-ray imaging machines has put forward higher requirements for the processing speed of enhancement systems. In this paper, an adaptive enhancement system consisting of a top control unit (TCU), an image quality feature extraction unit (FEU), a multilayer perception (MLP) unit and an adaptive image processing unit (IPU) is presented. Four image quality features as well as MLPs are proposed to detect image quality problems and control the image processing performance. For IPU, a novel fast contrast limited adaptive histogram equalization (FCLAHE) is proposed to accelerate the interpolation process. Modified guided filter, laplacian filter, gamma correction, and FCLAHE are integrated into the IPU. The proposed system is implemented in register transfer level (RTL) and demonstrated on field programmable gate array (FPGA). It runs at a clock frequency of 133 MHz and is capable of processing $1980\\times 1080$ images or videos with a high throughput of 127.35 Mpixels/s. Moreover, the proposed system offers the top image enhancement performance among the state-of-the-art implementations and its peak throughput is $37\\times$ higher than a personal computer (PC) with Core i7 8750H.","PeriodicalId":166178,"journal":{"name":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An FPGA Based Adaptive Real-Time Enhancement System for Dental X-rays\",\"authors\":\"Haoyang Sang, Junsong Zhang, Liyi Yao, Zhao Wang, Kunmeng Luo, Wumeng Yin, Meng You, Bo Gao\",\"doi\":\"10.1109/ICECE54449.2021.9674312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dental X-ray imaging which shows the clear internal structure of teeth is essential for diagnosis. However, the image details in both dark and bright regions are often hard to distinguish due to the misoperation and the limitation of dental Xray imaging machines. In addition, the emergence of some realtime X-ray imaging machines has put forward higher requirements for the processing speed of enhancement systems. In this paper, an adaptive enhancement system consisting of a top control unit (TCU), an image quality feature extraction unit (FEU), a multilayer perception (MLP) unit and an adaptive image processing unit (IPU) is presented. Four image quality features as well as MLPs are proposed to detect image quality problems and control the image processing performance. For IPU, a novel fast contrast limited adaptive histogram equalization (FCLAHE) is proposed to accelerate the interpolation process. Modified guided filter, laplacian filter, gamma correction, and FCLAHE are integrated into the IPU. The proposed system is implemented in register transfer level (RTL) and demonstrated on field programmable gate array (FPGA). It runs at a clock frequency of 133 MHz and is capable of processing $1980\\\\times 1080$ images or videos with a high throughput of 127.35 Mpixels/s. Moreover, the proposed system offers the top image enhancement performance among the state-of-the-art implementations and its peak throughput is $37\\\\times$ higher than a personal computer (PC) with Core i7 8750H.\",\"PeriodicalId\":166178,\"journal\":{\"name\":\"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECE54449.2021.9674312\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Electronics and Communication Engineering (ICECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECE54449.2021.9674312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An FPGA Based Adaptive Real-Time Enhancement System for Dental X-rays
Dental X-ray imaging which shows the clear internal structure of teeth is essential for diagnosis. However, the image details in both dark and bright regions are often hard to distinguish due to the misoperation and the limitation of dental Xray imaging machines. In addition, the emergence of some realtime X-ray imaging machines has put forward higher requirements for the processing speed of enhancement systems. In this paper, an adaptive enhancement system consisting of a top control unit (TCU), an image quality feature extraction unit (FEU), a multilayer perception (MLP) unit and an adaptive image processing unit (IPU) is presented. Four image quality features as well as MLPs are proposed to detect image quality problems and control the image processing performance. For IPU, a novel fast contrast limited adaptive histogram equalization (FCLAHE) is proposed to accelerate the interpolation process. Modified guided filter, laplacian filter, gamma correction, and FCLAHE are integrated into the IPU. The proposed system is implemented in register transfer level (RTL) and demonstrated on field programmable gate array (FPGA). It runs at a clock frequency of 133 MHz and is capable of processing $1980\times 1080$ images or videos with a high throughput of 127.35 Mpixels/s. Moreover, the proposed system offers the top image enhancement performance among the state-of-the-art implementations and its peak throughput is $37\times$ higher than a personal computer (PC) with Core i7 8750H.