https://scholars.lib.ntu.edu.tw/handle/123456789/639431
標題: | A 28.8-mW Accelerator IC for Dark Channel Prior-Based Blind Image Deblurring | 作者: | Chen, Po Shao Chen, Yen Lung Lee, Yu Chi Fu, Zih Sing CHIA-HSIANG YANG |
關鍵字: | Alternating minimization | blind image deblurring | Cameras | Channel estimation | CMOS integrated circuits | Energy efficiency | energy-efficient architecture | Estimation | hardware accelerator | Image restoration | Kernel | Wrapping | 公開日期: | 1-一月-2023 | 來源出版物: | IEEE Journal of Solid-State Circuits | 摘要: | This work presents an accelerator that performs blind deblurring based on the dark channel prior. The alternating minimization algorithm is leveraged for latent image and blur kernel estimation. A 2-D Laplace equation solver is embedded to reduce the latency by 56% for boundary wrapping. For latent image estimation, gradient data locality is employed to reduce the latency by 57%. A sorting engine is designed to reduce the latency in data access by 96% for calculating the dark channel. A pipelined mixed-radix 1-D fast Fourier transform (FFT) engine is used for efficient latent image estimation and blur kernel estimation. By employing image size approximation, 85% of additions and 97% of multiplications for FFT can further be saved. In the blur kernel estimator, a 2-D convolution engine with a parallel architecture is implemented, reducing the latency by 79%. The accelerator supports blur kernels of |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/639431 | ISSN: | 00189200 | DOI: | 10.1109/JSSC.2023.3344539 |
顯示於: | 電機工程學系 |
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