Description: 利用二维小波分析对一幅图象作2层小波分解,并在此基础上提取各层的低频信息实现图像的压缩.-The use of two-dimensional wavelet analysis of images for a 2-layer wavelet decomposition, and on this basis the low-frequency information extracted all levels to achieve image compression. Platform: |
Size: 2048 |
Author:龙活 |
Hits:
Description: 一幅原始图像,在获取和传输过程中,会受到各种噪声的干扰,使图像退化,质量下降. 退化会引起图像模糊,特征淹没,对分析图像不利.为了抑制噪声改善图像质量进行的处理称为图像平滑或去噪.利用高斯函数得到了图像平滑去除随机噪声中使用的平滑模板的一个较普遍的公式。该公式为图像平滑去除噪声提供了多种模板选择。针对不同的图像噪声水平，选取不同的模板，才能达到去除噪声的最理想的效果。文中给出了图像平滑的实现算法,显示结果验证了上述方法和结论。-Any picture would be affected by all kinds of noise during the course of acquisition and transition which would lead to the degradation of a picture. The image and the character of a picture indistinct which is an disadvantage for image analysis. The way for lower down the noise to improve the quality of the picture calls the smoothing of image or denoising . It can be accomplished in spatial domain and frequency domain. A more common formula of templates used in image smooth denoising is developed from Gauss function in order to offer more templates to be chosen when denoising images with random noise. For each image with different levels of noise, only one template corresponding to the level of this image noise is optimal when denoising this image. The methods of smoothing processing are given in this paper .And the showing results are presented and they validate the above formula and conclusions. Platform: |
Size: 633856 |
Author:朱华 |
Hits:
Description: 对每一路图像进行小波变换，分别到其水平、垂直、四十五度角方向的高频分量以及其低频分量，得到每路图像的小波金字塔；
按取较大值的原则对两幅图像的不同层次、不同特征层的信息图分别进行融合；
根据融合的各图像分量的小波序列，进行小波逆变换，得到最后的融合图像。
-Road images of each wavelet transform, respectively, to its horizontal, vertical, 45 degree angle the direction of high-frequency components as well as its low-frequency components obtained for each road image wavelet pyramid according to the principles of taking a larger value of the two images different levels of information mapping feature level fusion respectively the basis of integration of various components of the wavelet image sequences, inverse wavelet transform, to be the final fusion image. Platform: |
Size: 1024 |
Author:shentian |
Hits:
Description: 首先对两幅需要进行融合的图像完成小波变换，小波系数位于LL，LH，HL以及HH这4个频带。小波系数的绝对值越大，其对应于更为尖锐的灰度变化（即图像中的突出特征部分），在小波融合中，一个主要的思想便是判断两幅原始图像对应小波系数的绝对值大小。在变换域的每一个小波系数都取绝对值相对大的那一个，这样，便实现了在所有分辨率级别上的小波系数融合，并且新的小波系数完好地保存了更多的频带特征。所有融合后的图像可以通过对新的小波系数进行小波逆变换得到。-First two images need to complete the integration of wavelet transform, wavelet coefficients in the LL, LH, HL, and HH the four frequency bands. The greater the absolute value of wavelet coefficients, which correspond to the more acute the gray scale (ie, the prominent features of the image in part), the wavelet fusion, one of the main thought is to check two pieces of the original image corresponds to the absolute value of wavelet coefficients size. In each wavelet transform domain coefficients that take a relatively large absolute value, so that the resolution will be achieved at all levels of integration of the wavelet coefficients and wavelet coefficients of the new well-preserved features of more frequency bands. All images can be fused by the wavelet coefficients of the new inverse wavelet transform. Platform: |
Size: 881664 |
Author:aluily |
Hits:
Description: ：根据小波低频子带图像的轮廓模糊度和高频子带图像的细节信息量随小波分解层数增多而增多的规律，从图像熵
出发，提出了一种基于低频子带图像熵差的最佳小波分解层数选择法, 该方法通过计算不同分解层数下各低频子带的图像
熵差，选择最接近原始图像熵差的分解层数作为最佳分解层数。用多种基于小波变换的图像融合法分别对两组医学图像进
行仿真实验，结果表明根据该分解层数选择法得到的融合图像目视效果最好，与相关系数、峰值信噪比、模糊Chebyshev 距离
值等客观评价指标保持了很好的一致性。
-Abstract：According to the law that the contour fuzziness of the low-frequency sub-band and the detail information of the high-frequency
sub-band increase with the growth of the wavelet decomposition levels, an effect selection method of the optimal decomposition level is
proposed. Firstly, the difference of original image entropy is calculated. Then, the differences of the low-frequency sub-image entropy
based on different decomposition level are calculated. Finally, the decomposition level which makes the difference of the low-frequency
sub-image entropy closest to the difference of original image entropy is found. This level is the optimal decomposition level. To fuse
two groups of medical images, simulation experiments are done by use of the wavelet transform and the PCA transform based on wavelet.
The experimental result indicates that the fusion image used by the proposed method has the best subjective feeling of human being, and
it has very good compatibility to objective Platform: |
Size: 160768 |
Author:杨颜华 |
Hits:
Description: 二维图像信号的去噪步骤：
（1）二维图像信号的小波分解。选择合适的小波与恰当的分解层次N，并对待压缩的二维图像信号进行N层分解计算。
（2）对分解后的每一层高频系数，选择一个恰当的阈值，并对该层高频系数进行软阈值量化处理。
（3）二维图像信号的小波重构。用小波分解后的第N层近似（低频系数）和经过阈值量化处理后的各层细节（高频系数），对二维信号进行小波重构。-Two-dimensional image signal denoising steps: (1) two-dimensional image signal wavelet decomposition. Select the appropriate wavelet decomposition level and the appropriate N, and treatment of compressed N-layer two-dimensional image signal decomposition calculations. (2) of the decomposition of high-frequency coefficients of each layer, select an appropriate threshold, and high-frequency coefficients of the layer of soft threshold quantification. (3) Wavelet two-dimensional image reconstruction. Wavelet decomposition of the first N-layer approximation (low frequency factor) and through the quantification of threshold levels after the details (high frequency coefficients), two-dimensional wavelet reconstruction signal. Platform: |
Size: 4096 |
Author:lujun |
Hits:
Description: 通过统计视频图像各帧图像某像素在不同灰度级区间内的频数来提取背景图像-STATS video image each frame image of a certain pixel in a frequency within the interval of the different gray levels to extract a background image Platform: |
Size: 1024 |
Author:袁阳 |
Hits:
Search - frequency levels of image