Papers by parya zolfaghari
In this paper we have presented a numerical model to investigate the impact of the diffusion leng... more In this paper we have presented a numerical model to investigate the impact of the diffusion length of excitons and the layer thickness on the quantum efficiency of the organic bilayer solar cells. An organic solar cell composed of P3HT as the donor material and C60 as the acceptor and Al and ITO as the metallic electrodes is considered. Optical simulation is performed using FDTD method in order to obtain the electric field distribution and the absorption profile,then numerical modeling is performed by solving the exciton rate equation to calculate the quantum efficiency. Results shows that, although absorption efficiency increases with increasing thickness, quantum efficiency is decreased because of the limitation imposed by low diffusion length. Increasing the diffusion length of excitons leads more excitons to reach to the interface in their lifetime and consequently more free carriers are generated.
2021 IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SoC)
In this paper, we propose a novel design of image deblurring in the form of one-shot convolution ... more In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of Finite Impulse Response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the Point Spread Function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.
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Papers by parya zolfaghari