• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.271-279
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• 2009

The Moving Picture Experts Group (MPEG) and Video Coding Experts Group (VCEG) have developed a new standard that promises to outperform the earlier MPEG-4 and H.263 standards. The new standard is called H.264/AVC (Advanced Video Coding) and is published jointly as MPEG-4 Part 10 and ITU-T Recommendation H.264. In particular, the H.264/AVC intra prediction coding provides nine directional prediction modes for every $4{\times}4$ block in order to reduce spatial redundancies. In this paper, an ABS (Adaptive Bit Skip) mode is proposed. In order to achieve coding efficiency, the proposed method can remove the mode bits to represent the prediction mode by using the similarity of adjacent pixels. Experimental results show that the proposed method achieves the PSNR gain of about 0.2 dB in R-D curve and reduces the bit rates about 3.6% compared with H.264/AVC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.665-674
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• 2001

In this paper, a reduced complexity fillet to simultaneously suppress the blocking and ringing artifacts of compressed video sequence is addressed. A new one dimensional regularized function to incorporate the smoothness to its neighboring pixels into the solution is defined, resulting in very low complexity filter The proposed regularization function consists of two sub-functions that combine local data fidelity and local smoothing constraints. The regularization parameters to control the trade-off between the local fidelity to the data and the smoothness are determined by available overhead information in decoder, such as maroc-block type and quantization step size. In addition, the regularization parameters are designed to have the limited range and stored as look-up-table, and therefore, the computational cost to determine the parameters can be reduced. The experimental results show the capability and efficiency of the proposed algorithm.

• Smart Media Journal
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• v.2 no.2
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• pp.28-32
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• 2013

In this paper, we present a method to reduce complexity of depth modeling modes (DMM) that are used in the current 3D-HEVC standardization. DMM adds four modes to the existing HEVC intra prediction modes for accurate object edge representation in the depth map. Especially, Mode 3 requires distortion calculation of numerous pre-defined wedgelets, inducing high complexity. The proposed method employs absolute differences of neighboring pixels in the sides of the reference block to find high intensity changing positions. Based on such positions, the number of wedgelet candidates is reduced to six and distortion calculation is skipped for irrelevant wedgelets. Experimental results show complexity reduction by 3.1% on average, while maintaining similar coding performance.

• Journal of Advanced Navigation Technology
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• v.12 no.3
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• pp.273-279
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• 2008

In this paper, we proposed a watermarking algorithm by using difference matrix between successive blocks in the transform domain. In the preprocessing, original image is decomposed with 1-level sub-bands by DWT. Then, all sub-bands which are excepted the low-frequency bands are set to normalize and make a reference image after transforming inverse DWT. The statistic variance of successive blocks between the original image and the reference image are calculated and finally, watermark is embedded considering the local characteristic with respect to the high-frequence components. Experimental results showed that the proposed approach is robust and better invisible in such attacks as filtering, JPEG and noise addition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.209-212
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• 2007

Digital images are corrupted by noises, during signal acquisition and transmission. Amount those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. The conventional image restoration algorithms are mostly taken in simple noise environment, but they didn't perform very well in tempter noises environment. So a modified image restoration algorithm, which can remove complex noises by using the intensity differences and spatial distances between center pixel and its neighbor pixels as parameters, is proposed in this paper. Simulation results demonstrate that the proposed algorithm can't only remove AWGN and impulse noise separately, but also performs well in preserving details of images as edge.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.120-127
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• 2010

This paper presents a SR method using adaptive interpolation based on local gradient features to obtain a high quality SR image. In this method, the distance between the interpolated pixel and the neighboring valid pixel is considered by using local gradient properties. The interpolation coefficients take the local gradient of the LR images into account. The smaller the local gradient of a pixel is, the more influence it should have on the interpolated pixel. And the median filter is finally applied to reduce the blurring and noise of the interpolated HR image. Experiment results show the effectiveness of the proposed method in comparison with other methods, especially in the edge areas of the images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.338-340
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• 2012

In images, the edge is an important element to analyze characteristics of the image and has been used selectively at several applications. Even now, many researches to detect and take advantage of theses edges are underway and in initially to detect edges, methods using the relation of adjacent pixels are proposed. Characteristic of these methods is that the processing speed of the algorithms is fast, but the specific weighted values are applied to all the pixels regardless of the images equally. In recent years, the research of the edge detection algorithm to adapt according to the image has been actively underway, in order to complement the drawbacks of the existing methods. Therefore, in order to detect the edge excellent characteristics In this paper, we proposed algorithm using adaptive mask.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2259-2264
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• 2014

For edge detection methods, there are Sobel, Prewitt, Roberts and Canny edge detector, and these methods have insufficient detection characteristics in the image corrupted by the impulse noise. Therefore in this paper, in order to improve these disadvantages of the previous methods and to effectively detect the edge in the impulse noise environment, using the $5{\times}5$ mask, the noise factors within the $3{\times}3$ mask based on the central pixel is determined, and depending on its status, for noise-free it is processed as is, and if noise is found, by obtaining the estimated mask using the adjacent pixels of each factor, an algorithm that detects the edge is proposed.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.461-469
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• 2022

This paper presents a novel training data extraction approach using semi-supervised learning (SSL)-based classification without the analyst intervention for time-series land-cover mapping. The SSL-based approach first performs initial classification using initial training data obtained from past images including land-cover characteristics similar to the image to be classified. Reliable training data from the initial classification result are then extracted from SSL-based iterative classification using classification uncertainty information and class labels of neighboring pixels as constraints. The potential of the SSL-based training data extraction approach was evaluated from a classification experiment using unmanned aerial vehicle images in croplands. The use of new training data automatically extracted by the proposed SSL approach could significantly alleviate the misclassification in the initial classification result. In particular, isolated pixels were substantially reduced by considering spatial contextual information from adjacent pixels. Consequently, the classification accuracy of the proposed approach was similar to that of classification using manually extracted training data. These results indicate that the SSL-based iterative classification presented in this study could be effectively applied to automatically extract reliable training data for time-series land-cover mapping.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.18-29
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• 2012

Viola-Jones algorithm, a very effective real-time object detection method, uses Haar-like features to constitute weak classifiers. A Haar-like feature is made up of at least two rectangles each of which corresponds to either positive or negative areas and the feature value is computed by subtracting the sum of pixel values in the negative area from that of pixel values in the positive area. Compared to the conventional Haar-like feature which is made up of more than one rectangle, in this paper, we present a couple of new rectangular features whose feature values are computed either by the sum or by the variance of pixel values in a rectangle. By the use of these rectangular features in combination with the conventional Haar-like features, we can select additional features which have been excluded in the conventional Viola-Jones algorithm where every features are the combination of contiguous bright and dark areas of an object. In doing so, we can enhance the performance of object detection without any computational overhead.