Bilateral filter

About: Bilateral filter is a research topic. Over the lifetime, 3500 publications have been published within this topic receiving 75582 citations.

Bilateral pyramid based pansharpening of multispectral satellite images

Abstract: A new fusion method based on bilateral pyramid for multispectral and panchromatic images is presented The fused image is obtained by two different rules: substitutive and additive methods Bilateral pyramid is a multiscale decomposition method which decomposes an input image into a base layer representing the low frequency content and several detail layers representing the high frequency part of the image In substitutive method, both MS and PAN images are decomposed using bilateral pyramid The detail layers of the PAN image are added to the base layer of the MS image In additive method, the detail layers of the PAN image are directly added to the MS image The proposed method is compared with the widely used IHS (intensity-hue-saturation), ATWT substitutive and ATWT additive fusion methods The resulting images as well as evaluation metrics demonstrate that the proposed algorithm has better performance

A Refined Bilateral Filtering Algorithm Based on Adaptively-Trimmed-Statistics for Speckle Reduction in SAR Imagery

Abstract: This paper proposes a refined bilateral filtering algorithm based on adaptively trimmed-statistics (ATS-RBF) for speckle reduction in SAR imagery. The new de-speckling method is based on the bilateral filtering method, where the similarities of gray levels and the spatial location of the neighboring pixels are exploited. However, the traditional bilateral filter is not effective to reduce the strong speckle, which is often presented as impulse noise. The ATS-RBF designs an adaptive sample trimming method to properly select the samples in the local reference window and the trimming depth used for sample trimming is automatically derived according to the homogeneity of the local reference window. Furthermore, an alterable window size-based scheme is proposed to enhance the speckle noise smoothing strength in homogeneous backgrounds. Finally, bilateral filtering is applied using the adaptively trimmed samples. The ATS-RBF has an excellent speckle noise smoothing performance while preserving the edges and the texture information of the SAR images. The experiments validate the effectiveness of the proposed method using TerraSAR-X images.

Fast bilateral filter with arbitrary range and domain kernels

Abstract: In this paper, we present a fast implementation of the bilateral filter with arbitrary range and domain kernels. It is based on the fast bilateral filter approximation that uses uniform box domain kernel. Instead of using a single box kernel, multiple box kernels are used and combined optimally to approximate an arbitrary domain kernel. The method achieves better approximation of the bilateral filter compared to the single box kernel version with little increase in computational complexity.

Texture removal by pixel classification using a rotating filter

Abstract: In this paper, we present a new method for removing texture in images using a smoothing rotating filter From this filter, a bank of smoothed images provides pixel signals able to classify a pixel as a texture pixel, a homogenous region pixel or an edge pixel Then, we introduce a new method for anisotropic diffusion which controls accurately the diffusion near edge and corner points and diffuses isotropically inside textured regions Several results applied on real images and a comparison with anisotropic diffusion methods show that our model is able to remove the texture and control the diffusion

Real-Time Subpixel Fast Bilateral Stereo

Abstract: Stereo vision technique has been widely used in robotic systems to acquire 3-D information. In recent years, many researchers have applied bilateral filtering in stereo vision to adaptively aggregate the matching costs. This has greatly improved the accuracy of the estimated disparity maps. However, the process of filtering the whole cost volume is very time consuming and therefore the researchers have to resort to some powerful hardware for the real-time purpose. This paper presents the implementation of fast bilateral stereo on a state-of-the-art GPU. By highly exploiting the parallel computing architecture of the GPU, the fast bilateral stereo performs in real time when processing the Middlebury stereo datasets.