• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.233-239
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• 2016

Color enhancement basically deals with color manipulation in digital images. Recently, the technique has become widely used as a result of the increasing use of digital cameras. Retinex-based colorenhancement algorithms are a popular technique. In this paper, retinex with bilateral filtering is proposed to improve the quality of poorly illuminated images. Generally, it consists of three main steps: first, a retinex-based algorithm with color restoration; second, transformation mapping using histogram matching; and finally, smoothing the image using a bilateral filter. The experimental results demonstrate that the proposed method can successfully enhance image contrast while avoiding the halo effect and maintaining the color distribution in the image.

• Current Optics and Photonics
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• v.4 no.3
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• pp.200-209
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• 2020

We describe an approach that uses a bilateral filter to reduce the ringing artifact in motion-blurred restoration image. It takes into account the specific physical structure of the ringing artifact combined with the properties of the human visual system. To properly reduce the ringing artifact, each of the adjacent pixels is limited in a straight line which has a given direction. To protect the edges and the texture regions of an image, our algorithm divides the image into texture regions and flat regions, and the artifact reduction algorithm is only applied to the flat region. Finally, we use 8 typical images and 5 objective quality evaluation indices to evaluate our algorithm. Experimental results show that our algorithm can obtain better results in subjective visual effect and in objective image quality evaluation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.457-464
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• 2010

The haze removal algorithm using dark channel prior, which was proposed by He et al., is an efficient algorithm and presents impressive results. But its high memory and computational requirements limit its applications. In this paper, we propose a method to improve the memory usage and calculation speed. We notice that the matting process accounts for most calculation time, so we replace the matting process with a fast bilateral filtering scheme. Using the bilateral filter, we can reduce the memory usage, but its computational complexity is still high. To reduce the computational complexity as well, we adapt a hierarchical structure for the bilateral filtering. Experimental results show that the proposed algorithm can remove haze in a picture effectively, while requiring much less computations than the He et al.'s method.

• Nuclear Engineering and Technology
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• v.39 no.6
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• pp.725-730
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• 2007

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.270-273
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• 2013

잡음이 존재하는 환경에서 이미지의 경계와 디테일을 살리는 것은 잡음을 제거하는 것에 있어서 가장 중요한 요소중의 하나이다. 이를 위한 방법 중 한가지는 Bilateral 필터를 이용하여 영상 잡음 제거를 하면서 영상의 경계와 디테일을 보존하는 방법이다. Bilateral 필터의 이러한 특성 때문에 최근 Bilateral 필터를 통한 영상 잡음 제거에 대한 연구가 한창 진행되고 있다. 이에 본 논문은 Bilateral 필터의 장점인 경계와 디테일을 부각시키는 능력을 개선하기 위해 가장 간단하다고 많이 알려진 영상의 경계 검출 알고리듬을 이용하여 더욱 효과적인 Bilateral 필터를 통한 영상 잡음 제거를 연구 개발하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.206-208
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• 2010

We propose a retouching method that converts a photography taken by smartphone to a watercolor painting image using bilateral filtering and mean shift segmentation which are mostly used in image processing. The first step is to convert an input image to fit the screen resolution of smartphone. And next step is to weaken high frequency components of the image, while preserving the edge of image using the bilateral filtering. And after that we perform mean shift segmentation from the bilateral filtered image. We apply parameters of mean shift segmentation considering the processing speed of smartphone. Experimental result shows that our method can be applied to various types of image and bring better result.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.242-243
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• 2010

Reducing compression artifacts such as ringing and blocking is one of important issues to improve a visual quality of a JPEG compressed image. In this paper, we propose a new post processing technique based on bilateral filtering (BF), which is one of the techniques that are used to reduce compression artifacts. An important issue with the application of the BF is the selection of the filter parameters, which affects the result significantly. In this work, we suggest a new method to select the filter parameter automatically. In addition to artifact reduction using the BF, a contrast enhancement is performed to overcome the contrast loss problem due to compression. The experimental result shows that the proposed approach can alleviate the artifacts efficiently.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.135-136
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• 2017

When driving at night time environment, the whole body of transports does not visible to us. Due to lack of light conditions, there are only two options, which is clearly visible their taillights and break lights. To improve the recognition correctness of vehicle detection, we present an approach to vehicle detection and tracking using finding contour of the object on binary image at night time. Bilateral filtering is used to make more clearly on threshold part. To remove unexpected small noises used morphological opening. In verification stage, paired tail lights are tracked during their existence in the ROI. The accuracy of the test results for vehicle detection is about 93%.

• Journal of the Korea Computer Graphics Society
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• v.13 no.3
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• pp.7-10
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• 2007

We propose an image filtering technique that removes various image styles. To destylize a given image, we define image styles as repeated patterns existing in the image. For dll pixels of the image, we compute image styles as style vectors. We remove image styles by using bilateral filtering based on these style vectors. Destylization results show well smoothed images while preserving feature boundaries. Our method effectively removes image styles and reveals image structures clearly, and results can be applied to several applications such as texture transfer.