Search - frequency levels of image

Search - frequency levels of image - List

[Windows Develop] yuxiangchuli--pinghua DL : 0: 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.
Date : 2025-12-28 Size : 619kb User : 朱华
[Windows Develop] xiaoboronghe DL : 0: 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.
Date : 2025-12-28 Size : 861kb User : aluily