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dc.contributor.authorKumar R.-
dc.contributor.authorKumar Kaushik, Brajesh-
dc.contributor.authorRaman, Balasubramanian-
dc.contributor.authorSharma G.-
dc.identifier.citationIEEE Sensors Journal, 21(22): 25931-25940-
dc.description.abstractThe demand for image dehazing is ever-increasing in image sensor based outdoor systems such as self-driving vehicles, automatic driver assistance, and in highway monitoring and analytics. These applications require dedicated hardware solution to meet high frame-rate and low power constraints. Previously, a few prior based hardware dehazing methods have been presented. However, they produce artifacts in the restored images due to the failure of the underlying assumptions. To address this problem and to meet the stringent requirements, a data-driven image dehazing approach based on convolutional neural network (CNN) and dark channel prior (DCP) is proposed that automatically learns the important features and produces better results. The proposed method is hardware friendly and its hardware implementation is also presented. The design employs few line buffers to store activations and eliminates the requirement of off-chip memory like dynamic random-access memory (DRAM). Field programmable gate array (FPGA) and application specific integrated circuit (AISC) implementations show that the architecture is highly suitable for application scenarios with constrained computational resources, low memory, and tight power budget. The quantitative analysis shows more than 11% average PSNR improvement in image quality on standard datasets as compared to the state-of-the-art hardware methods while consuming comparable hardware resources and power. © 2001-2012 IEEE.-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.ispartofIEEE Sensors Journal-
dc.subjectHardware implementation-
dc.subjectimage dehazing-
dc.subjectlightweight CNN-
dc.subjectreal-time processing-
dc.titleA Hybrid Dehazing Method and its Hardware Implementation for Image Sensors-
dc.affiliationKumar, R., Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, India-
dc.affiliationKaushik, B.K., Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, India-
dc.affiliationRaman, B., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, India-
dc.affiliationSharma, G., Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States-
dc.description.correspondingauthorKumar, R.; Department of Electronics and Communication Engineering, Uttarakhand, India; email:
Appears in Collections:Journal Publications [CS]

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