Search - 2d convolution

Search - 2d convolution - List

[Communication] 2D_convolution DL : 0: 二维卷积运算之C语言实现若x为N1*M1的二维信号，y为N2*M2的二维信号，则卷积为(N1+N2-1)*(M1+M2-1)的信号-2D convolution operators on C language if x N1 * M1 to the two-dimensional signal y * M2 N2 for the two-dimensional signal, convolution (N1 N2-1) * (M1 M2 - 1) signal
Update : 2008-10-13 Size : 3.33kb Publisher : 劉昱楓
[Special Effects] filterbutterworth DL : 0: 1.这是一个matlab滤波程序，内含空域二维卷积滤波；频域高通滤波；三级butterworth高通滤波器设计。 2.效果较好，内含较为翔实的代码注释，通用性，可移植性较强。-1. This is a Matlab filtering procedures, airspace containing 2D convolution filter; Frequency - domain high pass filter; 3 butterworth high pass filter design. 2. The result is better and more informative containing the code notes, general, portability strong.
Update : 2008-10-13 Size : 1001byte Publisher : 方周
[Communication] 2D_convolution DL : 0: 二维卷积运算之C语言实现若x为N1*M1的二维信号，y为N2*M2的二维信号，则卷积为(N1+N2-1)*(M1+M2-1)的信号-2D convolution operators on C language if x N1* M1 to the two-dimensional signal y* M2 N2 for the two-dimensional signal, convolution (N1 N2-1)* (M1 M2- 1) signal
Update : 2025-02-19 Size : 3kb Publisher : 劉昱楓
[Algorithm] Experiment-for-FFT-convolution-using-Overlap-Add-m DL : 0: 采用FFT和IFFT的快速卷积的C程序实现源代码。-FFT and IFFT fast convolution C program source code.
Update : 2025-02-19 Size : 2kb Publisher : minytian
[Special Effects] filterbutterworth DL : 0: 1.这是一个matlab滤波程序，内含空域二维卷积滤波；频域高通滤波；三级butterworth高通滤波器设计。 2.效果较好，内含较为翔实的代码注释，通用性，可移植性较强。-1. This is a Matlab filtering procedures, airspace containing 2D convolution filter; Frequency- domain high pass filter; 3 butterworth high pass filter design. 2. The result is better and more informative containing the code notes, general, portability strong.
Update : 2025-02-19 Size : 1kb Publisher : 方周
[Special Effects] fwt2d_demo DL : 0: 小波变换源码，国外VC开发的，效果比较好 I ve been involved with wavelet-analysis since my Ph.D studies and over the years developed various wavelet-transforms C++ libraries. This one concerns 2D implementation of the Fast wavelet transform (FWT). The 2D FWT is used in image processing tasks like image compression, denoising and fast scaling. I intended to design the implementation of the 2D FWT with custom filter support and simple in usage. I ve equipped it with known filter families: Daubechies, Coiflets and Biorthogonal wavelets. The wavelets used in compression tasks are Bior53 and Bior97. With Daub1 filter you can achieve fast dyadic image scaling algorithm. You may also experiment with other filters for compression and denoising and compare the results, you may also add your custom wavelets. The nice feature of this library is that reconstruction FWT filters are rearranged the way that you perform just convolution operations on the spectrum, which is very important if you d like MMX -err
Update : 2025-02-19 Size : 97kb Publisher :
[Other] conv2d DL : 0: 2d convolution on image
Update : 2025-02-19 Size : 133kb Publisher : Varun
[MPI] convolutionFFT2D DL : 0: 基于fft的2d旋转 FFT-based 2D convolution-FFT-based 2D convolution
Update : 2025-02-19 Size : 316kb Publisher : xiangxingbin
[matlab] gaborcon DL : 0: these codes read input image and generate the 2D gabor filters, with changeable scale, orientation, perform the convolution with input image.
Update : 2025-02-19 Size : 1kb Publisher : gayatri_mirajkar
[Special Effects] 1111 DL : 0: 数字图象处理教程 INTRODUCTION 4 DIGITAL IMAGE DEFINITIONS 5 COMMON VALUES 6 CHARACTERISTICS OF IMAGE OPERATIONS 7 TYPES OF OPERATIONS 7 TYPES OF NEIGHBORHOODS 8 VIDEO PARAMETERS 9 TOOLS 9 CONVOLUTION 10 PROPERTIES OF CONVOLUTION 10 FOURIER TRANSFORMS 10 PROPERTIES OF FOURIER TRANSFORMS 11 IMPORTANCE OF PHASE AND MAGNITUDE 14 CIRCULARLY SYMMETRIC SIGNALS 15 EXAMPLES OF 2D SIGNALS AND TRANSFORMS 15 STATISTICS 16 PROBABILITY DISTRIBUTION FUNCTION OF THE BRIGHTNESSES 16 PROBABILITY DENSITY FUNCTION OF THE BRIGHTNESSES 16 AVERAGE 18 STANDARD DEVIATION 19 COEFFICIENT-OF-VARIATION 19 PERCENTILES 19-INTRODUCTION 4 DIGITAL IMAGE DEFINITIONS 5 COMMON VALUES 6 CHARACTERISTICS OF IMAGE OPERATIONS 7 TYPES OF OPERATIONS 7 TYPES OF NEIGHBORHOODS 8 VIDEO PARAMETERS 9 TOOLS 9 CONVOLUTION 10 PROPERTIES OF CONVOLUTION 10 FOURIER TRANSFORMS 10 PROPERTIES OF FOURIER TRANSFORMS 11 IMPORTANCE OF PHASE AND MAGNITUDE 14 CIRCULARLY SYMMETRIC SIGNALS 15 EXAMPLES OF 2D SIGNALS AND TRANSFORMS 15 STATISTICS 16 PROBABILITY DISTRIBUTION FUNCTION OF THE BRIGHTNESSES 16 PROBABILITY DENSITY FUNCTION OF THE BRIGHTNESSES 16 AVERAGE 18 STANDARD DEVIATION 19 COEFFICIENT-OF-VARIATION 19 PERCENTILES 19 MODE 20 SIGNALTONOISE RATIO 20 CONTOUR REPRESENTATIONS 21 CHAIN CODE 21 CHAIN CODE PROPERTIES 22 CRACK CODE 22 RUN CODES 23 PERCEPTION 23 BRIGHTNESS SENSITIVITY 23 WAVELENGTH SENSITIVITY 24 STIMULUS SENSITIVITY 24 SPATIAL FREQUENCY SENSITIVITY 25 COLOR SENSITIVITY 26 STANDARD OBSERVER 26 CIE CHROMATICITY COORDINATES 26 OPTICAL ILLUSIONS 28 IMAGE SAMPLING 30 SAMPLING DENSITY FO
Update : 2025-02-19 Size : 2.52mb Publisher : sean
[Special Effects] convolve DL : 0: 常用图象处理matrices. 在用于2D convolution 中非常有用的。 -commonly used image processing convolution matrices.
Update : 2025-02-19 Size : 6kb Publisher : Magic
[matlab] matlabPyrTools DL : 1: This package contains some MatLab tools for multi-scale image processing. Briefly, the tools include: - Recursive multi-scale image decompositions (pyramids), including Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These operate on 1D or 2D signals of arbitrary dimension. Data structures are compatible with the MatLab wavelet toolbox. - Fast 2D convolution routines, with subsampling and boundary-handling. - Fast point-operations, histograms, histogram-matching. - Fast synthetic image generation: sine gratings, zone plates, fractals, etc. - Display routines for images and pyramids. These include several auto-scaling options, rounding to integer zoom factors to avoid resampling artifacts, and useful labeling (dimensions and gray-range). -This package contains some MatLab tools for multi-scale image processing. Briefly, the tools include: - Recursive multi-scale image decompositions (pyramids), including Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These operate on 1D or 2D signals of arbitrary dimension. Data structures are compatible with the MatLab wavelet toolbox. - Fast 2D convolution routines, with subsampling and boundary-handling. - Fast point-operations, histograms, histogram-matching. - Fast synthetic image generation: sine gratings, zone plates, fractals, etc. - Display routines for images and pyramids. These include several auto-scaling options, rounding to integer zoom factors to avoid resampling artifacts, and useful labeling (dimensions and gray-range).
Update : 2025-02-19 Size : 1.97mb Publisher : not applicable
[DSP program] conv2d DL : 0: Convolution 2D C code
Update : 2025-02-19 Size : 136kb Publisher : mkg081000
[Graph program] show2Dconvt DL : 0: 2D convolution c-code. it is used for 2D image processing .
Update : 2025-02-19 Size : 1kb Publisher : sooah yoon
[2D Graphic] convolve2 DL : 0: CONVOLVE2可以用于任何CONV2使用，采取同样的参数并返回一个小的公差范围内同样结果。加速计算是通过使用面膜中的奇异值分解，表示为外产品总结一下。这些都可以有效地计算与行和列向量的卷积。 CONV2是用来从事这项运动。可分面具是一个特殊情况，并受CONVOLVE2处理多达FILTER2一样。许多不属于其他口罩可分低等级（如Gabor函数口罩），并更有效地处理CONVOLVE2。该功能也将计算出降秩逼近一个给定的面具如果需要的话，将使用此是否会加速计算。一个额外的参数允许在错误控制。附加形状选项允许：（一）2 - D“的通知“执行卷积- 也就是说，输入数组被视为周期，而不是零包围（二）一个“反思“的边界条件- 那就是，输入数组被视为体现了自身的副本包围。看到计算机和机器人视觉第一卷，由R.M. Haralick和L.G.夏皮罗（Addison - Wesley出版1992年），第298-299 -CONVOLVE2 can be used wherever CONV2 is used, taking the same arguments and returning the same results to within a small tolerance. The computation is speeded up by using the singular value decomposition of the mask to express it as a sum of outer products. Each of these can be computed efficiently as convolution with a row and a column vector. CONV2 is used to carry this out. Separable masks are a particular case and are handled by CONVOLVE2 much as FILTER2 does. Many other masks which are not separable have low rank (e.g. Gabor function masks) and are handled more efficiently by CONVOLVE2. The function will also compute a reduced-rank approximation to a given mask if required and will use this if it will speed up the computation. An extra argument allows control over the error. Additional shape options allow: (a) 2-D "circular" convolution to be performed- that is, the input array is taken to be periodic rather than surrounded by zeros (b) a "reflection" boundary c
Update : 2025-02-19 Size : 6kb Publisher : namind
[Industry research] Convolution DL : 0: Convolution of 1D and 2D image
Update : 2025-02-19 Size : 280kb Publisher : Surajit
[VHDL-FPGA-Verilog] Convolution_filter-fpga DL : 0: Implementation of a 2D Convolution Filter on FPGA. Performance evaluation between CPU, GBU and FPGA
Update : 2025-02-19 Size : 51kb Publisher : Birrax
[DSP program] filter2Dconv DL : 0: filter 2D convolution code
Update : 2025-02-19 Size : 1kb Publisher : Swe
[Other] 2D-reflection-wave DL : 0: 二维反射波，多次覆盖，用雷克子波褶积，C++小程序-Two-dimensional reflection wave, many covered with a the Ricker wave of convolution, C++ applet
Update : 2025-02-19 Size : 229kb Publisher : 杰帅
[Other] A memory and area‑efficient distributed arithmetic based modular VLSI architecture of 1D/2D reconfigurable 9/7 and 5/3 D DL : 0: In this article, we have proposed the internal architecture of a dedicated hardware for 1D/2D convolution-based 9/7 and 5/3 DWT filters, exploiting bit-parallel ‘distributed arithmetic’ (DA) to reduce the computation time of our proposed DWT design while retaining the area at a comparable level to other recent existing designs. Despite using memory extensive bitparallel DA, we have successfully achieved 90% reduction in the memory size than that of the other notable architectures. Through our proposed architecture, both the 9/7 and 5/3 DWT filters can be realized with a selection input, mode. With the introduction of DA, we have incorporated pipelining and parallelism into our proposed convolution-based 1D/2D DWT architectures. We have reduced the area by 38.3% and memory requirement by 90% than that of the latest remarkable designs. The critical-path delay of our design is almost 50% than that of the other latest designs. We have successfully applied our prototype 2D design for real-time image decomposition. The quality of the architecture in case of real-time image decomposition is measured by ‘peak signal-to-noise ratio’ and ‘computation time’, where our proposed design outperforms other similar kind of software- and hardware-based implementations.
Update : 2021-10-05 Size : 3.28mb Publisher : nalevihtkas

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