guided filer

导向滤波器是一种图像滤波技术，通过对图像进行分层和分解，可以增强图像细节和边缘的保留，同时有效地去除图像噪声。导向滤波器的基本思想是根据图像的结构信息和属性，调整滤波器的系数，以避免在滤波过程中过度平滑或过度锐化图像。相比于传统的线性滤波器，导向滤波器可以更好地处理复杂的图像情况，同时保留更多的图像细节信息。导向滤波器广泛应用于计算机视觉、图像处理、图像分析等领域，逐渐成为一种重要的图像滤波技术。

相关问题

guided backpropagation

引导反向传播（guided backpropagation）是一种深度学习中的可视化技术，它可以帮助我们理解神经网络中的决策过程。它通过将反向传播算法中的梯度限制在正值区间内，来突出显示神经网络中对于特定输入的激活区域。这样可以帮助我们更好地理解神经网络中的决策过程，以及哪些输入对于网络的决策起到了关键作用。

guided diffusion

Guided diffusion is a deep learning algorithm that is used for image denoising and image inpainting tasks. It is based on the concept of diffusion processes, where the image is modeled as a diffusion of information through a set of random walks. The algorithm is guided by a conditioning image, which provides additional information to the diffusion process. This conditioning image can be any image that is related to the input image, such as a corrupted version of the input image or a semantic segmentation map.

Guided diffusion is a generative model, which means that it can be used to generate new images. By randomly sampling from the diffusion process, the algorithm can generate new images that are similar to the input image but have different details or textures. This makes it a useful tool for image synthesis tasks, such as generating realistic images of objects or scenes.

Guided diffusion has been shown to achieve state-of-the-art performance on several image denoising and inpainting benchmarks, and it has been applied to a wide range of image processing tasks, including super-resolution, colorization, and style transfer.