• International journal of advanced smart convergence
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• v.9 no.3
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.131-136
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• 2005

Motion Estimation (ME) has been developed to remove redundant data contained in a sequence of image. And ME is an important part of video encoding systems, since it can significantly affect the qualify of an encoded sequences. Generally, ME consists of two stages, the integer pixel motion estimation and the half pixel motion estimation. Many methods have been developed to reduce the computational complexity at the integer pixel motion estimation. However, the studies are needed at the half pixel motion estimation to reduce the complexity. In this paper, a method based on the correlations between integer pixel motion vectors and half pixel motion vectors is proposed for the half pixel motion estimation. The proposed method has less computational complexity than the full half pixel search method (FHSM) that needs the bilinear interpolation of half pixels and examines nine half pixel points to the find the half pixel motion vector. Experimental results show that the speedup improvement of the proposed method over FHSM can be up to $2.5\~80$ times faster and the image quality degradation is about to $0.07\~0.69(dB)$.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.411-417
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• 2006

Motion Estimation (ME) is an important part of video coding process and it takes the largest amount of computation in video compression. Half-pixel and quarter-pixel motion estimation can improve the video compression rate at the cost of higher computational complexity In this paper, we suggest a new efficient low-complexity algorithm for half-pixel and quarter pixel motion estimation. It is based on the experimental results that the sum of absolute differences(SAD) shows parabolic shape and thus can be approximated by using interpolation techniques. The sub-pixel motion vector is searched from the minimum SAD integer-pixel motion vector. The sub-pixel search direction is determined toward the neighboring pixel with the lowest SAD among 8 neighbors. Experimental results show that more than 20% reduction in computation time can be achieved without affecting the quality of video.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.26-28
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• 2007

The motion estimation is the most important technique in the image compression of the video standards. In the case of next generation standards in the video codec as H.264, a high compression-efficiency can be also obtained by using a motion compensation. To obtain the accurate motion search, a motion estimation should be achieved up to 1/2 pixel and 1/4 pixel uiuts. To do this, the computational complexity is increased although the image compression rate is increased. Therefore, in this paper, we propose the advanced sub-pixel block matching algorithm to reduce the computational complexity by using a statistical characteristics of SAD(Sum of Absolute Difference). Generally, the probability of the minimum SAD values is high when searching point is in the distance 1 from the reference point. Thus, we reduced the searching area and then we can overcome the computational complexity problem. The main concept of proposed algorithm, which based on TSS(Three Step Search) method, first we find three minimum SAD points which is in integer distance unit, and then, in second step, the optimal point is in 1/2 pixel unit either between the most minimum SAD value point and the second minimum SAD point or between the most minimum SAD value point and the third minimum SAD point In third step, after finding the smallest SAD value between two SAD values on 1/2 pixel unit, the final optimized point is between the most minimum SAD value and the result value of the third step, in 1/2 pixel unit i.e., 1/4 pixel unit in totally. The conventional TSS method needs an eight.. search points in the sub-pixel steps in 1/2 pixel unit and also an eight search points in 1/4 pixel, to detect the optimal point. However, in proposed algorithm, only total five search points are needed. In the result. 23 % improvement of processing speed is obtained.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.1006-1009
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• 2003

In a motion estimation method for use in encoding a moving picture, a full-pixel motion vector is estimated by stochastically sampling a pixel to be processed in a predetermined-sized block of a previous frame or a next frame as a reference frame for each of a plurality of equal-sized blocks in a current frame. Then, a half-pixel motion vector is estimated based on the full-pixel motion vector. Accordingly, both the calculation amount and the calculation time required for the motion estimation are effectively reduced. Further, it can be prevented that the hardware becomes complicated. .

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.977-984
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• 2019

This paper proposes a single image dehazing that utilizes the transmission estimation with low complexity and the pixel-based JBDCP (Joint Bright and Dark Channel Prior) for the effective application of hazy outdoor images. The conventional transmission estimation includes the refinement process with high computational complexity and memory requirements. We propose the transmission estimation using combination of pixel- and block-based dark channel information and it significantly reduces the complexity while preserving the edge information accurately. Moreover, it is possible to estimate the transmission reflecting the image characteristics, by obtaining a different air-light for each pixel position of the image using the pixel-based JBDCP. Experimental results on various hazy images illustrate that the proposed method exhibits excellent dehazing performance with low complexity compared to the conventional methods; thus, it can be applied in various fields including real-time devices.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.383-384
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• 2007

In this paper, we propose the new and simple method for sub-pixel block search algorithm by only using integer-pixel for motion estimation and compensation. In many papers, the fast search block match algorithms based on TSS have been proposed. However, these methods could be achieved a little reduction of the computational complexity. All of searching points by 1/4-pixel have own predicted integer-pixel SAD array. Therefor, if we know initial nine SAD values by integer, which is on the searching area of the reference frame, then we can find optimal searching point by 1/4-pixel, directly.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.327-328
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• 2007

A contour shape matching based pixel motion estimation is proposed. The pixel motion information is very useful to compensate the motion artifact generated at the specific gray level contours in the moving image for subfield gray-scale display devices. In this motion estimation method, the gray level boundary contours are extracted from the input image. Then using contour shape matching, the most similar contour in next frame is found, and the contour is divided into segment unit. The pixel motion vector is estimated from the displacement of the each segment in the contour by segment matching. From this method, more precise motion vector can be estimated and this method is more robust to image motion with rotation or from illumination variations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1813-1820
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• 2000

In this paper we proposed an efficient multiresolution motion estimation(MRME) algorithm using half-pixel accuracy motion estimation (HPAME) and characteristics of motion vectors in the baseband. Conventional MRME method needs exact motion vectors in the baseband because those are used as initial motion vectors in higher frequency subbands. Therefore the proposed method uses HPAME to estimate the motion vectors exactly in the baseband. Based on the characteristics of these motion vectors the motion vectors in the higher frequency subbands are selectively estimatied. That is motion vectors in the higher frequency subbands are estimated only for the blocks which have the half-pixel accuracy motion vectors in the baseband. In the proposed method by using HPAME in the baseband and selective motion estimation in the higher frequency subbands we can obtain reconstructed image with the similar quality with the conventional method though we reduce the computational complexity and the bit rate considerably.