• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.43-48
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• 2011

Among various methods proposed earlier, fuzzy image filtering is usually one of the favored techniques because it has less blurring effect and the decrease of noise removal rate after filtering. However, fuzzy filtering is ineffective on color images since it is firstly developed with gray scale. Thus, in this paper, we propose a fuzzy filtering algorithm for color images. First, we divide RGB color information from image into three channels of R, G, and B and judge the possibility of each pixel with mask by fuzzy logic independently. The output pixel value might be the average or median according to the degree of noise. Our experiment successfully verifies the effectiveness of new algorithm in color image.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.647-650
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• 2013

HEVC RExt(High Efficiency Video Coding Range Extension) set a goal to support RGB/YUV 4:2:2 4:4:4 color sampling and over 10 bit-depth images. Unlike the previous 4:2:0 color sampling images, RGB images have the high correlation in inter-color planes. Using this characteristic, some methods which are contributed in JCT-VC standardization meetings estimate the pixel values of inter-color plane. But when we use the estimation of inter-color plane in RGB images, high frequency components of RGB images are caused to reduce the coding efficiency because they usually have the low inter-color plane correlation. Therefore, in this paper, we propose an adaptive low pass filtering method in the inter-color plane estimation. Using this method, we can improve the estimation efficiency of inter-color plane in RGB images. The experimental results with HEVC RExt RGB test sequences show that the proposed method has 0.6% BD(Bjontegaard Distortion)-rate gain and some increased complexity compared to the previous inter-color plane estimation method.

• Journal of Mechanical Science and Technology
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• v.14 no.1
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• pp.113-120
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• 2000

This study has developed a new liquid crystal calibration technique using Neural networks with median filtering and applied this technique to heat transfer measurements. To verify the validity of this new measurement technique, the local Nusselt numbers on a flat plate surface subjected to an axisymmetric impinging jet were measured and compared with the results by the conventional Hue-temperature calibration technique under the same conditions. Because the Neural networks predict the non-linear relations between temperatures and corresponding R, G, B values, Neural networks-median filtering calibration technique can utilize a much wider color band in the experiment than the Hue-temperature calibration technique, resulting in a significant reduction in the experimental time.

• 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.1
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• pp.16-22
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• 2020

In high resolution imaging devices, smaller aperture in the color filter causes cross talk which provides incorrect information. Plasmonic color filters (PCFs) have been reported as an alternative of the conventional color resist based-color filter (CRCF) and many studies on PCFs demonstrated the filtering function by PCFs with a sub-micron size. In this work, we investigated the cross talk performance of PCFs compared to CRCFs. The effect of cross talk over distance from the filter were measured for each filter. Despite poorer spectral filtering characteristics, PCFs were more robust against cross talk than CRCFs. Also, the further away from the filter, the more cross talk appeared. As a result, PCFs showed less cross talk than CRCFs at about 82% of the results measured at a distance of 2~10 ㎛. This study will help to make practical use of PCFs in high-resolution imaging applications.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.487-490
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• 1999

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based features. The color features are extracted from color histograms of the global image and the wavelet based features are extracted from the invariant moments of the high-pass band image through the spatial-frequency analysis of the wavelet transform. The proposed algorithm, called color and wavelet features based query(CWBQ), is composed of two-step query operations for efficient image retrieval: the coarse level filtering operation and the fine level matching operation. In the first filtering operation, the color histogram feature is used to filter out the dissimilar images quickly from a large image database. The second matching operation applies the wavelet based feature to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1464-1468
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• 2004

The color conversion and color enhancement on gray image is presented in this paper. The pseudocoloring for RCB color components extraction from gray image is used the 2D U(Fast Wavelet Transform) for fille. bank and re-array. The each post processing is used the median filtering for noise reduction and the discrete color histogram equalization for CIT(Color Intensity Transformation). The experiment result has enhanced pseudocoloring image as PSNR 30dB over compared the processing of normal wavelet transform.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.743-744
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• 2016

Object tracking in video sequences is a challenging task and has various applications. Particle filtering has been proven very successful for non-Gaussian and non-linear estimation problems. In this study, we first try to develop a color-based particle filter. In this approach, the color distributions of video frames are integrated into particle filtering. Color distributions are applied because of their robustness and computational efficiency. The model of the particle filter is defined by the color information of the tracked object. The model is compared with the current hypotheses of the particle filter using the Bhattacharyya coefficient. The proposed tracking method directly incorporates the scale and motion changes of the objects. Experimental results have been presented to show the effectiveness of our proposed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1021-1027
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• 2000

In this paper, we propose two new detection-estimation based algorithms that effectively remove impulsive noises in severely corrupted color images. The existing methods for enhancing corrupted color images with impulsive noises commonly possess the inherent problems of excessive computing time and smoothing out edges. However, since our proposed algorithms classify corrupted pixels first in each channel or in each pixel and then perform marginal or vector median filtering only for them, are computationally efficient and preserve edges well. In addition, since there are no appropriate criteria to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor to compare the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than the existing methods in terms of both objective and subjective evaluat ons.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.105-112
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• 2012

Face detection at a distance faces is very challenging since images are often degraded by blurring and noise as well as low resolution. This paper proposes an improved face detection method with AdaBoost filtering and sequential testing stages with color and shape information. The conventional AdaBoost filter detects face regions but often generates false alarms. The face detection method is improved by adopting sequential testing stages in order to remove false alarms. The testing stages comprise skin-color test and variable edge-mask filtering. The skin-color filtering is composed of two steps, which involve rectangular window regions and individual pixels to generate binary face clusters. The size of the variable edge-mask is determined by the ellipse which is estimated from the face cluster. The validation of the horizontal and vertical ratio of the mask is also investigated. In the experiments, the efficacy of the proposed algorithm is proved by images captured by a CCTV and a smart-phone