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Bilateral filter

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


Papers
More filters
Journal ArticleDOI
Miao Qi1, Hao Qiaohong1, Qingji Guan1, Jun Kong1, You Zhang1 
01 Nov 2015-Optik
TL;DR: Experimental results indicate that the proposed method can achieve comparable or even better dehazing results than several well-known methods in view of subjective and objective evaluations.

12 citations

Dissertation
01 Jan 2005
TL;DR: The standard linear signal and image processing methods in handling colour images using hypercomplex numbers and quaternion algebra are generalized to allow a systematic mathematical treatment of colour images as vector images.
Abstract: Quaternions have been a subject for research in mathematics, physical, and engineering for decades. Using quaternions to represent colours, however, has recently been proposed and studied. In this thesis, we wish to generalize the standard linear signal and image processing methods in handling colour images using hypercomplex numbers and quaternion algebra to allow a systematic mathematical treatment of colour images as vector images. The overall goal of this thesis is to explore and evaluate the role of quaternions in colour image analysis and processing. To begin with, the basic mathematical background of quaternions is reviewed and summarised, including quaternion arithmetic and the hypercomplex number family. Colour sensitive filtering can be achieved using a quaternion-valued filter, such that colours are smoothed only in a certain direction. There are two colour edge detection methods defined on quaternions. One is based on the chromaticity cancellation that generates a grey colour for nonboundary regions; the other is based on estimation of homogeneity of regions. Trilateral filtering is proposed to integrate the colour sensitive filter and the bilateral filter by locally adapting colour and changing the shape of the filter to achieve the effect of smoothing colours yet preserving edges. Binary quaternion-moment-preserving thresholding can be used to sharpen edges. Furthermore, quaternion Fourier analysis has been implemented efficiently by decomposition into complex Fourier equivalence, which allows convolution and cross-correlation on quaternionvalued images in the frequency domain. Additionally, quaternion wavelet transform based on Haar function will be introduced. Finally, based on quaternion singular value decomposition, quaternion principle analysis is implemented and applied to several applications, such as segmentation of colour images.

12 citations

Patent
16 Nov 2016
TL;DR: In this article, a fast bilateral filter in the shearlet transform was proposed to improve the denoising performance, and greatly increase the processing efficiency of denoised medical ultrasound images.
Abstract: The invention discloses a shearlet transform and fast bilateral filter image denoising method, which comprises the steps of: 1) acquiring an envelope signal of a noise image by using a noise imaging system, and establishing a medical ultrasonic image model; 2) carrying out multiscale and multidirectional decomposition on the medical ultrasonic image model after logarithmic transformation obtained in the step 1) by utilizing a pyramid filter bank; 3) performing threshold method contraction processing on a two-dimensional discrete shearlet transform coefficient of a high-frequency part in each subband image obtained in the step 2); 4) using a fast bilateral filter for filtering shearlet coefficients of low-frequency parts in the step 2); 5) and conducting shearlet inverse transform processing on all the coefficients processed in the step 3) and the step 4), so as to obtain a denoised medical ultrasound images. The introduction of the fast bilateral filter in the shearlet transform and fast bilateral filter image denoising method can effectively improve the denoising performance, and greatly increase the processing efficiency.

12 citations

Journal ArticleDOI
TL;DR: A novel interest point detection algorithm, which detects scale space extrema by using a Laplacian-of-Bilateral (LoB) filter, which can preserve edge characteristic by fully utilizing the information of intensity variety.
Abstract: Scale-invariant feature transform (SIFT) algorithm, one of the most famous and popular interest point detectors, detects extrema by using difference-of-Gaussian (DoG) filter which is an approximation to the Laplacian-of-Gaussian (LoG) for improving speed. However, DoG filter has a strong response along edge, even if the location along the edge is poorly determined and therefore is unstable to small amounts of noise. In this paper, we propose a novel interest point detection algorithm, which detects scale space extrema by using a Laplacian-of-Bilateral (LoB) filter. The LoB filter, which is produced by Bilateral and Laplacian filter, can preserve edge characteristic by fully utilizing the information of intensity variety. Compared with the SIFT algorithm, our algorithm substantially improves the repeatability of detected interest points on a very challenging benchmark dataset, in which images were generated under different imaging conditions. Extensive experimental results show that the proposed approach is more robust to challenging problems such as illumination and viewpoint changes, especially when encountering large illumination change.

12 citations

Proceedings ArticleDOI
25 Feb 2019
TL;DR: An image processing based pipeline for automated recognition and translation of pointer movement in analogue circular gauges based on the temporal estimations of the pointer angle is presented.
Abstract: This paper presents an image processing based pipeline for automated recognition and translation of pointer movement in analogue circular gauges. The proposed method processes an input video frame-wise in a module based manner. Noise is minimized in each image using a bilateral filter before a Gaussian mean adaptive threshold is applied to segment objects. Subsequently, the objects are described by a set of proposed features and classified using probability distributions estimated using Expectation Maximization. The pointer is classified by the Mahalanobis distance and the angle of the pointer is determined using PCA. The output is a low pass filtered digital time series based on the temporal estimations of the pointer angle. Seven test videos have been processed by the algorithm showing promising results. Both source code and video data are publicly available.

12 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202321
202257
2021116
2020145
2019203
2018204