• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.787-797
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• 2008

In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.197-204
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• 2006

Recent advances in information technology have resulted in rapid growth in the mobile communication. With this explosive growth, reliable transmission and error concealment technique become increasingly important to offer high quality multimedia services. In this paper, we propose an improved BMA(Boundary Matching Algorithm) method using gradient vectors to conceal channel errors in inter-frames of H.264 video images. General BMA method computes the sum of pixel differences of adjacent pixels of the candidate block and its neighbouring blocks, assuming that adjacent pixels have almost the same value. In real images, however, there exist some gradients, which means that the pixel values are increasing or decreasing in a specific direction. In this paper, we develop a precise estimation method of errors in candidates blocks using gradient information and try to recover lost blocks with this technique. Experimental results show the improvement of picture quality about $1{\sim}3dB$ compared to existing methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.734-740
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• 2017

A frame rate up-conversion scheme is needed when moving pictures with a low frame rate is played on appliances with a high frame rate. Frame rate up-conversion methods interpolate the frame with two consecutive frames of the original source. This can be divided into the frame repetition method and motion estimation-based the frame interpolation one. Frame repetition has very low complexity, but it can yield jerky artifacts. The interpolation method based on a motion estimation and compensation can be divided into pixel or block interpolation methods. In the case of pixel interpolation, the interpolated frame was classified into four areas, which were interpolated using different methods. The block interpolation method has relatively low complexity, but it can yield blocking artifacts. The proposed method is the frame rate up-conversion method based on a block motion estimation and compensation using the linearity of motion. This method uses two previous frames and one next frame for motion estimation and compensation. The simulation results show that the proposed algorithm effectively enhances the objective quality, particularly in a high resolution image. In addition, the proposed method has similar or higher subjective quality than other conventional approaches.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.238-247
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• 2002

In this paper, we propose an object-based stereo sequence compression technique using disparity-motion vector relationship. The proposed method uses the coherence of motion vectors and disparity vectors in the left and right Image sequences. After two motion vectors and one disparity vector ate computed using FBMA(Fixed Block Matching Algorithm), the disparity vector of the current stereoscopic pall is computed by disparity-motion vector relationship with vectors which are previously estimated. Moreover, a vector regularization technique is applied in order to obtain reliable vectors. For an object-based coding. the object is defined and coded in terms of layers of VOP such as in MPEG-4. we present a method using disparity and motion vector relationship for extending two-frame compensation into three-frame compensation method for prediction coding of B-VOP. The proposed algorithm shows a high performance when comparing with a conventional method.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.229-236
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• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.712-717
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• 2013

In this paper, we propose a performance-enhanced object recognition by using nonlinear 3D correlator based on pixel restoration. In the proposed method, elemental images of the 3D target that are partially occluded by a foreground object are picked up and transformed into sub-images. By using the block-matching algorithm, the occluded target regions of each sub-image are estimated and removed. After that, the missing pixels in each sub-image are reestablished by using the pixel-restoration method. Finally, through the nonlinear cross-correlations between the reconstructed reference and the target plane images, the improved object recognition can be performed. To show the feasibility of the proposed method, some preliminary experiments are carried out and results are presented by comparing the conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.611-617
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• 2004

This paper presents a simple method of rotational motion estimation and correction for roll axis stabilization of an image. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. Roll motion correction is then performed by the nearest neighbor interpolation technique. To show the effectiveness of our approach, the synthetic and real images are evaluated, resulting in better performance than the previous ones.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.887-890
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• 1998

We present a novel multi-resolution block matching algorithm (BMA) for fast motion estimation. At the coarsest level, a full search BMA (FSBMA) is performed for searching complex or random motion. Concurrently, spatial correlation of motion vector (MV) field is used for searching continuous motion. Here we present an efficient method for searching full resolution MVs without MV decimation even at the coarsest leve. After the coarsest level search, two or three initial MV candidates are chosen for the next level. At the further levels, the MV candidates are refined within much smaller search areas. Simulation results show that in comparison with FSBMA, the proposed BMA achieves a speed-up factor over 710 with minor PSNR degradation of 0.2dB at most, under a normal MPEG2 coding environment. Furthermore, our scheme is also suitable for hardware implementation due to regular data-flow.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.783-784
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• 2008

Block-matching motion estimation plays an important role in video coding. In this paper, we propose fast motion estimation algorithm using octagon pattern for low complexity. Proposed algorithm carries out minimum SAD point among nine regions divided by octagon pattern and center point. Experimental results show that proposed algorithm has better performance than conventional method through quantitative analysis.