Recently, two 2D algorithms for super resolution image reconstruction based on a matrix observation model were presented. They can greatly reduce computational cost and storage requirement but are suitable for the cas...
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Recently, two 2D algorithms for super resolution image reconstruction based on a matrix observation model were presented. They can greatly reduce computational cost and storage requirement but are suitable for the cases of face images or no warping operator. In this paper, for wide applications we propose a novel 2D algorithm to reconstruct a high-resolution image from multiple warped and degraded low-resolution images. The proposed 2D algorithm minimizes a new cost function with two regularization terms where one is the Laplacian regularization term for robustness to noise and another is learning term for more high frequency information. Simulation results show that the proposed 2D algorithm can obtain better results in terms of both PSNR and visual quality than the two existing 2D algorithms.
In this paper, a new algorithm used for implementing large-point DFT is proposed. This algorithm is called large-point discrete Fourier transform (LPDFT) algorithm. Firstly, when used to calculate a sequence with more...
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ISBN:
(纸本)9781538634608
In this paper, a new algorithm used for implementing large-point DFT is proposed. This algorithm is called large-point discrete Fourier transform (LPDFT) algorithm. Firstly, when used to calculate a sequence with more than 100K points, the multiplication number of LPDFT algorithm is reduced by 60% compared to the normal radix-2 FFT. When LPDFT algorithm is implemented in FPGA, the FPGA resource occupancy rate is significantly drop due to the significant reduction of the multiplication number. Secondly, due to the use of a two-dimensional algorithm, the index value of each dimension is significantly reduced. Since the Xilinx FPGA FFT IP core function can only support calculating up to 64K points of sequence, the reduction makes it possible to use the Xilinx FPGA FFT IP core function. Simulations show that the waveforms with more than 100K points implemented with LPDFT algorithm are identical in accuracy to the waveforms implemented with FFT algorithm.
The discrete cosine transform (DCT) has been successfully used for a wide range of applications in digital signal processing. While there are efficient algorithms for implementing the DCT, its use becomes difficult in...
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The discrete cosine transform (DCT) has been successfully used for a wide range of applications in digital signal processing. While there are efficient algorithms for implementing the DCT, its use becomes difficult in the sliding transform scenario where the transform window is shifted one sample at a time and the transform process is repeated. In this paper, a new two-dimensional sliding DCT (2-D SDCT) algorithm is proposed for fast implementation of the DCT on 2-D sliding windows. In the proposed algorithm, the DCT coefficients of the shifted window are computed by exploiting the recursive relationship between 2-D DCT outputs of three successive windows. The theoretical analysis shows that the computational requirement of the proposed 2-D SDCT algorithm is the lowest among existing 2-D DCT algorithms. Moreover, the proposed algorithm enables independent updating of each DCT coefficient. (C) 2016 Elsevier Inc. All rights reserved.
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