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Description: 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
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Size: 3409 |
Author: 劉昱楓 |
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Description: 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.
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Author: 方周 |
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Description: 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
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Size: 3072 |
Author: 劉昱楓 |
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Description: 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.
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Size: 2048 |
Author: minytian |
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Description: 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.
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Size: 1024 |
Author: 方周 |
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Description: 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
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Description: 2d convolution on image
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Size: 136192 |
Author: Varun |
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Description: 基于fft的2d旋转
FFT-based 2D
convolution-FFT-based 2D
convolution
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Size: 323584 |
Author: xiangxingbin |
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Description: these codes read input image and generate the 2D gabor filters, with changeable scale, orientation, perform the convolution with input image.
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Size: 1024 |
Author: gayatri_mirajkar |
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Description: 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
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Author: sean |
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Description: 常用图象处理matrices. 在用于2D convolution 中非常有用的。
-commonly used image processing convolution matrices.
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Author: Magic |
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Description: 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).
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Author: not applicable |
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Description: Convolution 2D C code
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Size: 139264 |
Author: mkg081000 |
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Description: 2D convolution c-code. it is used for 2D image processing .
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Size: 1024 |
Author: sooah yoon |
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Description: 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
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Author: namind |
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Description: Convolution of 1D and 2D image
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Size: 286720 |
Author: Surajit |
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Description: Implementation of a 2D Convolution Filter on FPGA. Performance evaluation between CPU, GBU and FPGA
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Size: 52224 |
Author: Birrax |
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Description: filter 2D convolution code
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Size: 1024 |
Author: Swe |
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Description: 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
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Author: 杰帅 |
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Description: 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.
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Author: nalevihtkas |
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