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Description: 利用傅里叶变换，在频域上对两幅图像配准，是一种比较配准的新方法，但是对弹性配准的效果不是很好 需要进一步的研究。-Registers two images (2-D rigid translation) within a fraction of a pixel specified by the user. Instead of computing a zero-padded FFT (fast Fourier transform), this code uses selective upsampling by a matrix-multiply DFT (discrete FT) to dramatically reduce computation time and memory without sacrificing accuracy
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Size: 5120 |
Author: wangwei |
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Description: DFT in matlab, the code is a example of long time in computation.
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Size: 1024 |
Author: Eymardh7 |
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Description: 采用OPENCV封装的图像二维DFT运算，通过该类可生成图像二维傅里叶变换矩阵，通过可选参数可调整生成傅里叶矩阵、傅里叶频谱同时可选择对数加强属性增强傅里叶频谱的显示效果。-OPENCV package using two-dimensional DFT computation of image, the image can be generated through such two-dimensional Fourier transform matrix generated by the optional parameter adjustable Fourier matrix, Fourier spectrum also can choose the number of enhancing properties of the enhanced fourier leaves the spectrum display.
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Size: 1024 |
Author: 葛世超 |
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Description: 计算dft的程序，可输出变换后序列到txt文件，并可显示计算时间-Dft calculation procedure, the transformed output sequence to the txt file, and may show the computation time
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Size: 609280 |
Author: ly |
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Description: FFT 并不是一种新的变换，它是离散傅立叶变换（DFT）的一种快速算法。由于我们在计算DFT 时一次复数乘法需用四次实数乘法和二次实数加法；一次复数加法则需二次实数加
法。每运算一个X（k）需要4N 次复数乘法及2N+2（N-1）=2（2N-1）次实数加法。所以
整个DFT 运算总共需要4N^2 次实数乘法和N*2(2N-1)=2N(2N-1)次实数加法。如此一来，计算时乘法次数和加法次数都是和N^2 成正比的，当N 很大时，运算量是可观的，因而需要
改进对DFT 的算法减少运算速度。-FFT is not a new transformation, it is the discrete Fourier transform (DFT) of a fast algorithm. Since we have a complex multiplication when calculating DFT Xuyong four real multiplications and real additions secondary a complex quadratic addition Zexu real addition. Each operator of a X (k) requires 4N times complex multiplication and 2N+2 (N-1) = 2 (2N-1) times the real number addition. Therefore, the DFT computation requires 4N ^ 2 times in total real multiplications and N* 2 (2N-1) = 2N (2N-1) times the real number addition. Thus, when calculating the number of multiplications and additions and are proportional to N ^ 2, when N is large, the computation is considerable and, therefore, need to improve on the DFT algorithm to reduce computational speed.
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Size: 404480 |
Author: 平意义 |
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Description: 基8-DFT计算，每8点为一蝶形运算单元，4096点计算效率较基2-DFT提高50 -Yl 8-DFT calculation, every 8 points for a butterfly operation unit, the 4096-point computation efficiency than the base 2-DFT increased by 50
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Size: 1024 |
Author: ZLD |
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Description: A Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DFT) and its inverse. There are many distinct FFT algorithms involving a wide range of mathematics, from simple complex-number arithmetic to group theory and number theory. The fast Fourier Transform is a highly efficient procedure for computing the DFT of a finite series and requires less number of computations than that of direct evaluation of DFT. It reduces the computations by taking advantage of the fact that the calculation of the coefficients of the DFT can be carried out iteratively. Due to this, FFT computation technique is used in digital spectral analysis, filter simulation, autocorrelation and pattern recognition.
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Size: 2048 |
Author: Quoc Viet Ta |
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Description: The FFT is based on decomposition and breaking the transform into smaller transforms and combining them to get the total transform. FFT reduces the computation time required to compute a discrete Fourier transform and improves the performance by a factor of 100 or more over direct evaluation of the DFT.
A DFT decomposes a sequence of values into components of different frequencies. This operation is useful in many fields but computing it directly from the definition is often too slow to be practical. An FFT is a way to compute the same result more quickly: computing a DFT of N points in the obvious way, using the definition, takes O( N2 ) arithmetical operations, while an FFT can compute the same result in only O(N log N) operations.
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Size: 10240 |
Author: Quoc Viet Ta |
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Description: The FFT is based on decomposition and breaking the transform into smaller transforms and combining them to get the total transform. FFT reduces the computation time required to compute a discrete Fourier transform and improves the performance by a factor of 100 or more over direct evaluation of the DFT.
A DFT decomposes a sequence of values into components of different frequencies. This operation is useful in many fields but computing it directly from the definition is often too slow to be practical. An FFT is a way to compute the same result more quickly: computing a DFT of N points in the obvious way, using the definition, takes O( N2 ) arithmetical operations, while an FFT can compute the same result in only O(N log N) operations.
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Size: 166912 |
Author: Quoc Viet Ta |
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Description: The FFT is based on decomposition and breaking the transform into smaller transforms and combining them to get the total transform. FFT reduces the computation time required to compute a discrete Fourier transform and improves the performance by a factor of 100 or more over direct evaluation of the DFT.
A DFT decomposes a sequence of values into components of different frequencies. This operation is useful in many fields but computing it directly from the definition is often too slow to be practical. An FFT is a way to compute the same result more quickly: computing a DFT of N points in the obvious way, using the definition, takes O( N2 ) arithmetical operations, while an FFT can compute the same result in only O(N log N) operations.
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Size: 659456 |
Author: Quoc Viet Ta |
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Description: This paper proposes a hybrid architecture
algorithm for fast computation of DCT and DFT via
recursive factorization. Recursive factorization of DCT-II
and DFT transform matrix leads to a similar architectural
structure so that common architectural base may be used by
simply adding a switching device. Linking between two
transforms was derived based on matrix recursion
formula. Also computational complexity is comparable to
those of the fast DCT algorithms for moderate size of N.
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Size: 164864 |
Author: fia4joy |
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Description: 利用傅里叶变换，在频域上对两幅图像配准，是一种比较配准的新方法，但是对弹性配准的效果不是很好 需要进一步的研究。-Registers two images (2-D rigid translation) within a fraction of a pixel specified by the user. Instead of computing a zero-padded FFT (fast Fourier transform), this code uses selective upsampling by a matrix-multiply DFT (discrete FT) to dramatically reduce computation time and memory without sacrificing accuracy
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Size: 5120 |
Author: nsionlo |
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Description: Pipeline FFT processor is a specified class of processors for DFT computation utilizing fast algorithms
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Size: 142336 |
Author: Manish Bansal |
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Description: 1) Goertzel algorithm
2) Chirp transform algorithm
3) Verification of signal flow graphs for DIT and DIF FFT algorithm
4) Elapsed CPU time for DFT and FFT computation
5) Alternative IDFT computations
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Size: 346112 |
Author: |
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Description: The Fast Fourier Transform (FFT) is one of the
rudimentary operations in field of digital signal and image
processing. Some of the very vital applications of the fast
fourier transform include Signal analysis, Sound filtering, Data
compression, Partial differential equations, Multiplication of
large integers, Image filtering etc.Fast Fourier transform
(FFT) is an efficient implementation of the discrete Fourier
transform (DFT). This paper concentrates on the development
of the Fast Fourier Transform (FFT), based on Decimation-In-
Time (DIT) domain, Radix-2 algorithm, this paper uses VHDL
as a design entity, and their Synthesis by Xilinx Synthesis Tool
on Vertex kit has been done. The input of Fast Fourier
transform has been given by a PS2 KEYBOARD using a
testbench and output has been displayed using the waveforms
on the Xilinx Design Suite 12.1.The synthesis results show that
the computation for calculating the 32-point Fast Fourier
transform is efficient in terms of speed.
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Size: 305152 |
Author: doggaravi |
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Description: COMPUTATION OF DFT SEQUENCES
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Size: 1024 |
Author: nagesh |
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Description: 实现功能：基8实现64点FFT处理器（进行两次8点FFT计算，采用基8进行64点）
详细说明：硬件结构包括六部分，分别为输入模块、8点FFT模块、乘法模块、顺序调整模块、输出模块和总控制模块。
其中，输入模块的主要功能是将串行输入的64个数据进行分类，分成8批次，每次8个输入到8点FFT模块中进行计算。
8点FFT模块：FFT是DFT的快速算法，当点数较大时，可以较大的减少DFT的运算量。常用的FFT算法主要有两种，分别为按时间抽选的FFT算法（DIT-FFT）和按频率抽选的FFT算法（DIF-FFT）。在我们的设计中，我们采用的是按频率抽选的8点FFT算法。
乘法模块：由于旋转因子的对称性，只需要产生8个常数因子即可。但这样会复用一些单元，从而影响运算速度，为了提高计算速度，我们分析时序情况，增加了一些单元，以实现输入数据到达之后就可以进行运算。
顺序调整模块是将第一级FFT出来的数据顺序进行调整并输出到下一级FFT模块中进行计算，数据的顺序调整情况类似于输入模块，每隔8个数取一个输出。
输出模块：由于第二级FFT模块输出数据顺序不符合实际要求，因此需要调整数据的顺序，从而使64个输出数据安装顺序串行输出，结构类似于输入模块，区别只是输入变为8个数据并行，输出为一个数据串行。-Function: base 8 implement 64-point FFT processor (twice 8:00 FFT calculation, using the base 8 of 64 points)
Description: The hardware configuration consists of six parts, namely, an input module, 8-point FFT module, multiplication module, order adjustment module, the output module and total control module.
Among them, the 64 data input module is the main function of the serial input classification, divided into eight lots, each 8 inputs and 8-point FFT module calculation.
8:00 FFT module: FFT is a fast algorithm for DFT, when a large number of points, you can greatly reduce the amount of computation of the DFT. FFT algorithm commonly used mainly two were decimated by time FFT algorithm (DIT-FFT) algorithms and FFT decimation in frequency (DIF-FFT). In our design, we have adopted is based on the frequency of lottery 8:00 FFT algorithm.
Multiplication module: Since rotational symmetry factor, you only need to generate 8 constant factor. But it will reuse some of the units, which af
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Size: 32768 |
Author: 李圣华 |
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