• Journal of Korea Multimedia Society
• /
• v.5 no.1
• /
• pp.28-37
• /
• 2002

In this paper, we propose new methods used in MPEG codec that can improve the picture quality degradations of the reconstructed images, such as blocking artifacts, without additional computations. At first, a new 2-step MAD motion search is presented in the motion search and compensation course to reduce the computations and the errors of block boundary pixels. And we also present an overlapped 2-step MAD motion search that use the pixels beyond the block boundary using the reduced computations. In DCT/quantization course for intra-blocks, 1-D DCT predictive quantization and pixel difference predictive quantization, those use the adjacent pixel sets of the Previously reconstructed blocks and improve the inter-block continuity, are presented. As simulation results, proposed methods shows better picture qualities by reducing blocking artifacts than that of the conventional MPEG.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.689-698
• /
• 2017

In this paper, a new classification method based on the combination of semi-supervised learning with spatial similarity of adjacent pixels is presented for crop classification in inaccessible areas. Iterative classification based on semi-supervised learning is applied to extract reliable training data from both the initial classification result with a small number of training data, and classification results of adjacent pixels are also considered to extract new training pixels with less uncertainty. To evaluate the applicability of the proposed method, a case study of the classification of field crops was carried out using multi-temporal Landsat-8 OLI acquired in the Daehongdan region, North Korea. From a case study, the misclassification of crops and forests, and isolated pixels in the initial classification result were greatly reduced by applying the proposed semi-supervised learning method. In addition, the combination of classification results of adjacent pixels for the extraction of new training data led to the great reduction of both misclassification results and isolated pixels, compared to the initial classification and traditional semi-supervised learning results. Therefore, it is expected that the proposed method would be effectively applied to classify areas in which it is difficult to collect sufficient training data.

• Journal of Internet Computing and Services
• /
• v.18 no.1
• /
• pp.21-26
• /
• 2017

In this paper, an USB-OTG (Uiversal Serial Bus On-the-go) interface module was designed with the iris information for personal identification. The image recognition algorithm which was searching face and iris areas, was proposed with pixel differences from eye blinking after several facial images were captured and then detected without any activities like as pressing the button of smart phone. The region of pupil and iris could be fast involved with the proper iris area segmentation from the pixel value calculation of frame difference among the images which were detected with two adjacent open-eye and close-eye pictures. This proposed iris recognition could be fast processed with the proper grid size of the eye region, and designed with the frame difference between the adjacent images from the USB-OTG interface with this camera module with the restrict of searching area in face and iris location. As a result, the detection time of iris location can be reduced, and this module can be expected with eliminating the standby time of eye-open.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.483-488
• /
• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.9
• /
• pp.91-102
• /
• 1999

It is known that the digital image enlargement technique which only uses spatially neighbored pixels information in a still image can increase the size of the image but the practical enhancement of resolution is small because the frequency bandwidth of the image is basically limited. To solve this problem, this paper proposes the digital image enlargement technique that improves the reconstruction of the edge components by selectively transposing the direction of the subwindows of pseudomedian filter according to the distribution of neighbored pixels to the interpolation point. The pseudomedian filter has the better performance in aspect of the reconstruction of edge information when the pixel values masked by two subwindows parallel to the interpolation point are very similar and the pixel values masked by another subwindow that is orthogonal to the above two subwindows are similar to each other. In this paper, the computer simulation for digital image enlargement was performed with consideration of these characteristics when selecting the subwindows of pseudomedina filter. Based on this simulation result, the performance of the proposed method was analysed and its effectiveness was assessed. According to the proposed method, visual artifacts that result from using the limited samples can be effectively suppressed, and most characteristics and shapes of the original image can be preserved as well.

• Journal of Korea Multimedia Society
• /
• v.6 no.1
• /
• pp.40-47
• /
• 2003

In this paper, we propose a new method for reducing the computational overhead of fine-to-coarse multi-resolution motion estimation (MRME) at the finest resolution level by searching for the region to consider motion vectors of the coarsest resolution subband. At this time, if half-pel accuracy motion estimation (HPAME) is used in the baseband where influence a lot of effect to the reconstructed image, we can have the motion vector exactly But, this method causes to higher computational overhead. So we suggest the method to the computational overhead by using selective interpolation. Experimental results show that the proposed algorithm gives better results than the traditional algorithms from image quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.11a
• /
• pp.63-66
• /
• 2009

기존의 H.264/AVC 비디오 표준은 고화질 비디오 부호화를 지원하지만 고해상도에 특화된 요소 기술이 도입되지 않아 만족할만한 성능을 보이지 못한다. 현존하는 동영상 압축 표준 중 가장 뛰어난 H.264/AVC 표준의 인트라 $16{\times}16$ 예측은 매크로블록에 인접한 최대 33개의 주변 화소를 이용하여 매크로블록에 속한 256개의 화소 값을 예측한다. 특히, 전체 예측 모드 중 수직과 수평 예측 모드에서는 16개의 수직 또는 수평 위치에 위치한 주변 화소로 전체 매크로블록 내의 화소 값을 예측하므로 매크로 블록의 끝으로 갈수록 예측의 정확도가 떨어져 부호화 비트가 증가한다. 고화질 영상에서는 인트라 $16{\times}16$ 모드로 부호화되는 블록이 많으므로 수행되므로 인트라 $16{\times}16$ 예측의 정확도를 높일 수 있는 기술이 필요하다. 본 논문에서는 기존의 H.264/AVC의 예측 방법보다 예측 정확도가 높은 새로운 라인 기반 $16{\times}16$ 인트라 예측 방법을 제안한다. 일반적으로 편평한 특성을 보이는 인트라 $16{\times}16$ 블록이라도 좀 더 가까운 화소를 참조 화소로 사용하면 예측의 정확도를 높여 부호화 비트를 줄일 수 있다. 이를 이용하여 제안하는 알고리즘에서는 인트라 $16{\times}16$ 블록에서 16개 화소 한 줄을 단위로 예측 및 부호화를 수행한다. 1080p HD급 테스트 영상을 이용하여 실험한 결과, 기존의 H.264/AVC FRExt High 프로파일에 비해 평균 약 6.92%의 부호화 비트를 감소시킬 수 있음을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.12C
• /
• pp.738-743
• /
• 2011

For the high quality 3-D broadcasting, depth maps are important data. Although commercially available depth cameras capture high-accuracy depth maps in real time, their resolutions are much smaller than those of the corresponding color images due to technical limitations. In this paper, we propose the depth map up-sampling method using a high-resolution color image and a low-resolution depth map. We define a random walk probability model in an operation unit which has nearest seed pixels. The proposed method is appropriate to match boundaries between the color image and the depth map. Experimental results show that our method enhances the depth map resolution successfully.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8A
• /
• pp.669-678
• /
• 2012

In this paper, we propose an efficient fast integer-pel motion estimation for H.264/AVC using local statistics of local motion vectors. Using neighboring motion vectors, we define a new statistical property that is used to determine a mode of motion search range of current block. In addition, an adaptive motion search range compensated method that is based on cumulative statistics of previous coded blocks is addressed to solve the problem of the statistical motion search range decision method. Experimental results show that proposed algorithm has the capability to reduce the computational cost over the other methods.

• Journal of IKEEE
• /
• v.10 no.1 s.18
• /
• pp.87-95
• /
• 2006

This paper presents the analyses of the effect of inserting border lines between different color regions on edge detection in color codes, and is not intended to present any new algorithm for color-code recognition. With its role to complement the RFID (radio frequency identification) and the wide and fast spread of digital cameras, an interest on color codes is fast increasing. However, the severe distortion of colors in obtained images prohibits color codes from expanding their applications. To reduce the effect of color distortion it is desirable to process the whole pixels in each color region statistically, instead of relying on some pixels sampled from the region. This requires segmentation, and the segmentation usually requires edge detection. To help detect edges not disconnected, we inserted border lines of the width of two pixels between adjacent color regions. Two colors were used for the border lines: one consisting of white pixels, and the other black pixels. The edge detection was performed on images with either of the two kinds of border lines inserted, and the results were compared to results without inserted border lines. We found that inserting black border lines degraded edge detection by causing zipper effect while inserting white border lines improved it compared to the cases without inserted border lines.