• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.10-12
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• 2014

This work is based on the motion estimation to handle the ill-posed nature. The algorithm used in this study that performs the motion estimation for overlapped block is used to calculate with using pixel of neighborhood block with higher correlation and present block by considering the correlation level of neighborhood block. The proposed method shows in a significant improvement in the quality of the mothion field when comparing the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.692-702
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• 2001

In this paper, a new block-matching algorithm for standard video encoder is proposed. The algorithm finds a motion vector using the increasing SAD transition curve for each predefined candidates, not a coarse-to-fine approach as a conventional method. To remove low-probability candidates at the early stage of accumulation, a dispersed accumulation matrix is also proposed. This matrix guarantees high-linearity to the SAD transition curve. Therefore, base on this method, we present a new fast block-matching algorithm with the slice competition technique. The Candidate Selection Step and the Candidate Competition Step makes an out-performance model that considerably reduces computational power and not to be trapped into local minima. The computational power is reduced by 10%~70% than that of the conventional BMAs. Regarding computational time, an 18%~35% reduction was achieved by the proposed algorithm. Finally, the average MAD is always low in various bit-streams. The results were also very similar to the MAD of the full search block-matching algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.611-615
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• 2009

Due to the popular use of digital camera, a great number of photos are taken at every usage of camera. It is essential to reveal relationship between photos to manage digital photos efficiently. We propose a method that tessellates image into unit blocks and applies 2D alignment to extend content-based similar region from seed block pair having high similarity. Through an alignment, we can get a block region scoring best matching value on whole image. The method can distinguish whether photos are sharing the same object or background. Our result is less sensitive to transition or pause change of objects. In experiment, we show how our alignment method is applied to real photo and necessities for further research like photo clustering and massive photo management.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.231-233
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• 2009

The object recognition is one of the major computer vision fields. The object recognition using features(SIFT) is finding common features in input images and query images. But the object recognition using feature methods has suffered of difficulties due to heavy calculations when resizing input images and query images. In this paper, we focused on speed up finding features in the images. we proposed method using block segmentation and histogram. Block segmentation used diving input image and than histogram decided correlation between each 1]lock and query image. This paper has confirmed that tile matching time reduced for object recognition since reducing block.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.321-326
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• 2019

Image denoising methods based on block matching are founded on the experimental observations that neighboring patches or blocks in images retain similar features with each other, and have been proved to show superior performance in denoising different kinds of noise. The methods, however, take into account only neighboring blocks in searching for similar blocks, and ignore the characteristic features of the reference block itself. Consequently, denoising performance is negatively affected when outliers of the Gaussian distribution are included in the reference block which is to be denoised. In this paper, we propose an expanded block matching method in which noisy images are first decomposed into a number of bit-planes, then the range of true signals are estimated based on the distribution of pixels on the bit-planes, and finally outliers are replaced by the neighboring pixels belonging to the estimated range. In this way, the advantages of the conventional Gaussian filter can be added to the blocking matching method. We tested the proposed method through extensive experiments with well known test-bed images, and observed that performance gain can be achieved by the proposed method.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.403-406
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• 1999

Among the compression methods of moving picture information, a motion estimation method is used to remove time-repeating. The Block Matching Algorithm in motion estimation methods is the commonest one. In recent days, it is required the more advanced high quality in many image processing fields, for example HDTV, etc. Therefore, we have to accomplish not by means of Partial Search Algorithm, but by means of Full Search Algorithm in Block Matching Algorithm. In this paper, it is suggested a structure that reduce total calculation quantity and size, because the structure using Bit Plane select and use only 3bit of 8bit luminance signal.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.102-111
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• 1999

In this paper, we propose a fast full search block matching algorithm using the search region subsampling and the difference of adjacent pixels in current block. In the proposed algorithm, we calculate the lower bound of mean absolute difference (MAD) at each search point using the MAD value of neighbor search point and the difference of adjacent pixels in current block. After that, we perform block matching process only at the search points that need block matching process using the lower bound of MAD at each search point. To calculate the lower bound of MAD at each search point, we need the MAD value of neighbor search point. Therefore, the search points are subsampled at the factor of 4 and the MAD value at the subsampled search points are calculated by the block matching process. And then, the lower bound of MAD at the rest search points are calculated using the MAD value of the neighbor subsampled search point and the difference of adjacent pixels in current block. Finally, we discard the search points that have the lower bound of MAD value exceed the reference MAD which is the minimum MAD value of the MAD values at the subsampled search points and we perform the block matching process only at the search points that need block matching process. By doing so, we can reduce the computation complexity drastically while the motion compensated error performance is kept the same as that of full search block matching algorithm (FSBMA). The experimental results show that the proposed method has a much lower computational complexity than that of FSBMA while the motion compensated error performance of the proposed method is kept same as that of FSBMA.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.537-543
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• 2015

Liquid crystal displays (LCDs) have slow responses, so motion blurs are often perceived in fast moving scenes. To reduce this motion blur, we propose a novel method of robust motion compensated frame interpolation (MCFI) based on bidirectional motion estimation (BME) and weight-overlapped block motion compensation (WOBMC) with variable block sizes. In most MCFI methods, a static block size is used, so some block artefacts and motion blurs are observed. However, the proposed method adjusts motion block sizes and search ranges by comparing matching scores, so the precise motion vectors can be estimated in accordance with motions. In the MCFI, overlapping ranges for WOBMC are also determined by adjusted block sizes, so the accurate MCFI can be performed. In the experimental results, the proposed method strongly reduced motion blurs arisen from large motions, and yielded interpolated images with high visual performance and peak signal-to-noise ratio (PSNR).

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1563-1571
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• 2009

In this paper, we propose a new boundary matching method for the temporal error concealment and a post processing algorithm for perceptual quality improvement of the concealed frame. Temporal error concealment is a method that substitutes error blocks with similar blocks from the reference frame. In conventional H.264/AVC standard, it compares outside pixels of erroneous block with inside pixels of reference block to find the most similar block. However, it is very possible that the conventional method substitutes erroneous block with the wrong one because it compares only narrow spatial range of pixels. In this paper, for substituting erroneous blocks with more correct blocks, we propose enhanced boundary matching method by comparing inside and outside pixels of reference block with outside pixels of erroneous block and setting up additional candidate motion vector in the fixed search range based on maximum and minimum value of candidate motion vectors. Furthermore, we propose a post processing method to smooth edges between concealed and decoded blocks without error by using the modified deblocking filter. We identified that the proposed method shows quality improvement of about 0.9dB over the conventional boundary matching methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.45-55
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• 1993

In this paper, a two-stage block matching algorithm (BMA), which can reduce greatly the computational complexity of the conventional BMAs, is proposed, in which the onedimensional distortion measure based on the integral projection is introduced to determine the candidate motion vectors and then among them a final motion vector is detected based on the conventional two-dimensional distortion measure. Due to the one-dimensional calculation of a distortion measure, the proposed algorithm can reduce the computational complexity of the conventional BMA (full search method with a 16$\times$16 block) by a factor of 4, with its performance comparable to those of the conventional ones. Simulation results based on the original and noisy image sequences are shown. Also the simulation of the proposed method combined with the MPEG (Moving Picture Experts Group) SM3 (Simulation Model Three) is presented. Computer simulation shows that the proposed algorithm is fast with its performance comparable to those of the conventional ones.