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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
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Journal ArticleDOI
Jiawan Zhang1, Liang Li1, Guoqiang Yang1, Yi Zhang1, Jizhou Sun1 
TL;DR: The results demonstrate that the proposed algorithm can produce transmission maps without being affected by the local albedo variations and, furthermore, recover haze-free images.
Abstract: In this paper, we present a new algorithm to remove haze from a single image. The proposed algorithm extracts transmission iteratively under the assumption that large-scale chromaticity variations are due to transmission while small-scale luminance variations are due to scene albedo. A nonlinear edge-preserving filter is introduced to incrementally refine subtle transmission map while still keeping sharp transmission map distinct. The algorithm is verified by both synthetic images and real-scene photographs. The results demonstrate that our method can produce transmission maps without being affected by the local albedo variations and, furthermore, recover haze-free images. On top of haze removal, several applications of the transmission map including refocusing and relighting are also implemented.

39 citations

Journal ArticleDOI
TL;DR: A novel single-image based dehazing framework is proposed to remove haze artifacts from images through local atmospheric light estimation using a novel strategy based on a physical model where the extreme intensity of each RGB pixel is used to define an initial atmospheric veil.

39 citations

Patent
Remo J. D'Ortenzio1
04 Aug 1980
TL;DR: A separable two dimensional Finite Impulse Response (FIR) digital image processing filter with X-dimension filter section having a delay buffer series to which digitized image signals or pixels are first input.
Abstract: A separable two dimensional Finite Impulse Response (FIR) digital image processing filter with X-dimension filter section having a delay buffer series to which digitized image signals or pixels are first input. The buffer inputs and output are tapped and pixels tapped off are processed by preset multiplier factors and input to an adder where the processed pixels are summed. The summed pixels are fed to a line buffer series of a Y-dimension filter section, tapped off from the filter inputs and output, and processed by further preset multiplier factors. The processed pixels are input to a second adder and summed to provide filtered output pixels. In a second embodiment, the filter is symmetric and has a center point response of unity. In a third embodiment, the filter X and Y dimension filter sections are reversed.

39 citations

Patent
20 Mar 2002
TL;DR: In this paper, an information amount converting circuit enlarges an image obtained by the CCD with 270 or 190 thousand pixels in a horizontal direction and a vertical direction by using pixel interpolation.
Abstract: With a device that connects a processor device to electronic endoscopes having CCDs with different numbers of pixels, for example, 410, 270, or 190 thousand pixels mounted thereon, all the CCDs are driven at a frequency corresponding to 410 thousand pixels. Further, an information amount converting circuit enlarges an image obtained by the CCD with 270 or 190 thousand pixels in a horizontal direction and a vertical direction by using pixel interpolation. That is, data on a pixel to be interpolated is calculated by averaging pixels around this pixel, and enlarged binary data on this target pixel is obtained. A weighting factor is applied to this binary data, and the resultant data is added to the target pixel data. This process forms an image with an aspect ratio of 4:3.

38 citations

Patent
18 Oct 2001
TL;DR: In this article, an optimal filter kernel, formed by convolving a box filter with a filter of fixed integer width and unity area, is used to perform image resizing and reconstruction, and the output pixel values are calculated by multiplying the pixel value for each pixel under the kernel by the area of the standard filter kernel surrounding the pixel.
Abstract: An optimal filter kernel, formed by convolving a box filter with a filter of fixed integer width and unity area, is used to perform image resizing and reconstruction. The optimal filter has forced zeros at locations along a frequency scale corresponding to the reciprocal of the spacing of one or more pixels that comprise a source image to be resized. When a rescale value for a source image is selected, the optimal filter kernel is computed, mapped to the source image, and centered upon a location within the source image corresponding to the position of an output pixel to be generated. The number of pixels that lie underneath the optimal filter kernel is established by multiplying the number of pixels that comprise the width of the source image by the selected rescale value. Upon mapping the optimal filter kernel, the output pixel values that comprise the resized image are then evaluated by processing the one or more source image pixels, such as through interpolation. Alternatively, the output pixel values of the resized image are calculated by performing partial integral analysis with respect to a standard filter kernel of fixed width and unity area. The output pixel values are calculated by multiplying the pixel value for each pixel under the kernel by the area of the standard filter kernel surrounding the pixel. The products are then summed to reveal the output pixel value, and placed into the output image buffer. Both of these methods speed up the computation process, while producing a ripple free output image.

38 citations


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