• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.159-167
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• 2013

In stereo-view system, variations of target camera position or lighting conditions cause discrepancies on the luminance and chrominance components of stereo views. These discrepancies lead to inaccurate frame view prediction and low quality of 3 D video coding. In this paper, an efficient histogram interval calibration method is proposed for stereo-view coding, so as to compensate for the luminance component of target view. First the proposed method is analyzed by the histogram of the target image frame. Then, it divide two sections of histogram of that frame to correct the color discrepancies. Secondly, each section of the target frame is corrected the luminance component by identify the maximum matching region between the reference frame and the target frame. We have verified our proposed histogram matching method in comparison with the other color correction ones. Experimental results show that it can correct better luminance calibration results of PSNR(Peak Signal to Noise Ratio) and has less computation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.119-126
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• 2005

We propose a new content-based image retrieval using a representative color histogram and directional pattern histogram that is adaptive to the classification characteristics of the image blocks. In the proposed method the color and pattern feature vectors are extracted according to the characteristics o: the block classification after dividing the image into blocks with a fixed size. First, the divided blocks are classified as either luminance or color blocks depending on the saturation of the block. Thereafter, the color feature vectors are extracted by calculating histograms of the block average luminance co-occurrence for the luminance block and the block average colors for the color blocks. In addition, block directional pattern feature vectors are extracted by calculating histograms after performing the directional gradient classification of the luminance. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.16-18
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• 2012

Haze is an extreme reason of the reduction of contrast when capturing image in the outdoor. Recently, there are several single image dehazing techniques, but they are not robust in dynamic variations of natural environment caused by the thickness, coverage of haze and appearance of sunlight. In this paper, we propose an effective and robust method to enhance luminance for image dehazing depending on histogram analysis. Compare with conventional methods, our proposal have better performance in term of contrast, and computation time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.3-5
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• 2013

We proposed a method for increasing visibility of dehazed images by enhancing luminance component of dehazed image. For this purpose, we analyze shape of luminance histogram in multi bunches and observe that increasing visibility those bunches does not bear over contrast enhancement. From the analysis and observation, histogram equalization intends to increase visibility of each bunch with less computation.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.808-816
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• 2017

360 VR video systems has become important to provide immersive effect for viewers. The system consists of stitching, projection, compression, inverse projection, viewport extraction. In this paper, an efficient luminance compensation technique for 360 VR video sequences, where feature extraction and histogram equalization algorithms are utilized. The proposed luminance compensation algorithm enhance the performance of stitching in 360 VR system. The simulation results showed that the proposed technique is useful to increase the quality of the displayed image.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.10-21
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• 2016

Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.532-536
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• 2016

Frame Rate Up Conversion (FRUC) generate interpolated frames between existing frames using motion estimation and motion compensation interpolation considering temporal redundancy. Falsely-estimated FRUC, however, can generate poor quality frames because FRUC typically uses blending-based interpolation method. As skipping an interpolating process between frames generate mis-estimated motion vectors, could improve Quality of Services of FRUC. In this Paper we analyze luminance histogram and motion vector consistency in frames generating poor quality interpolated frames. We conclude these features could help to be a clue in classifying the frames, which often result in the poor quality of FRUC results through the analysis and experiment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.322-324
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• 2013

Haze is an extreme reason of the reduction of contrast when capturing image in the outdoor. Recently, there are several single image dehazing techniques, but they are not robust in dynamic variations of natural environment caused by the thickness, coverage of haze and appearance of sunlight. In this paper, we propose an effective and robust method to enhance luminance for image dehazing depending on histogram analysis. Compare with conventional methods, our proposal have better performance in term of contrast, and computation time.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.35-39
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• 2013

H.264/AVC is an authoritative international video coding standard which shows code and efficiency more improved than the existing video standards. Above all, the parameter block mode of H.264/AVC significantly contributes much to high compression efficiency. However, as the occasion demands, users tend to pass while overlooking the part that can produce a little higher compression efficiency. We, taking notice of this point, are designed to bring in much higher compression efficiency by gathering up the overlooked parts. This paper suggests the algorithm that produces efficient performance improvement by using the histogram of luminance in the pixel unit (Macroblock) of respective prediction block and applying specific thresholds. The experimental results proves that the technique proposed by this paper increases the compression efficiency of the existing H.264/AVC algorithm by 0.4% without any increase in the whole encoding time and PSNR complexity.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.304-308
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• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.