Single image dehazingFrequency-domain processingUnsupervised learningUnpaired dataHaze-free images have become a prerequisite for many computer vision tasks; therefore, single image dehazing is particularly important in the field. However, existing deep learning dehazing methods face the following problems: ...
2019-10-24 Computer Graphics / Image processing 研一上学期课程比较繁重,加上在实验室要做的事情也多,所以最近博客都没更新了。最近数图课上到频域变换处理相关章节,其中的傅里叶变换其实在图形学领域也有颇多的应用(例如大规模的海水模拟),遂写下这篇博客整理了一些关于傅里叶变换的内容。 复数域 傅里叶变换...
Note:Note:ifMandNareevennumbers,thentheshiftedcoordinateswillbeintegers.integers.2.computerF(u,v),theDFToftheimagefrom(1)利用离散傅立叶变换，利用离散傅立叶变换，将图像从空间域中转换到频率域中 7 Basicstepsforfilteringinthefrequencydomain3.multiplyF(u,v)byafilterfunctionH(u,v)对频率域中的图像进行...
Frequency-domain analysis is widely used in such areas as communications, geology, remote sensing, and image processing. While time-domain analysis shows how a signal changes over time, frequency-domain analysis shows how the signal's energy is distributed over a range of frequencies. A frequency...
In this paper, we propose a novel molten image enhancement and fusion method based on image decomposition in frequency domain. The algorithm combines the guided filter to maintain the original edge and details and to make it show a more permeable visual effect. Firstly, the high-quality molten ...
Learning in the Frequency Domainarxiv.org/abs/2002.12416 Abstract 深度神经网络在计算机视觉任务中取得了显着的成功。 现有的神经网络主要在具有固定输入大小的空间域中运行。 对于实际应用场景中,图像尺寸通常很大,必须下采样到神经网络的预定输入大小。 尽管下采样操作减少了计算量和所需的通信带宽,但它却无意...
今天又复习了一遍<<Digital Image Processing>>的第四章,为了加深对频域的理解,我自己用PS画了一张图。如下: 然后做FFT,得到频谱图如下: 从左到右依次表示:图像的频谱、频谱图往横轴的投影、频谱图往纵轴的投影。原图与频谱图的关系可以从两个角度来理解: ...
DSP - Introduction to Frequency-Domain Analysis Introduction Frequency-domain analysis is a tool of utmost importance in signal processing applications. Frequency-domain analysis is widely used in such areas as communications, geology, remote sensing, and image processing. Whiletime-domain analysis shows...
Inspired by the observation that human visual system (HVS) has unequal sensitivity to different frequency components [11], we analyze the image classification, detection and segmentation task in the frequency domain and find that CNN models are more sensitive to low-frequency channels than the high...
Frequency-domain analysis is a tool of utmost importance in signal processing applications. Frequency-domain analysis is widely used in such areas as communications, geology, remote sensing, and image processing. While time-domain analysis shows how a signal changes over time, frequency-domain analysis...