Frame rate up-conversion method based on texture adaptive bilateral motion estimation

Kim, Jinhyung; Ko, Yun-Ho; Kang, Hyun‐Soo; Lee, Si-Woong; Kwon, Jae Wan

doi:10.1109/tce.2014.6937329

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…1, although the true motion trajectory determines the correct MV to be MV1 and not MV2, the ME method selects MV2 based on the MV with the minimum BSAD value. To overcome this problem, the texture adaptive bilateral method (TABE) was proposed [5]. In TABE, SBAD is compensated for by an additional cost value that considers the texture of the interpolated image at each search point.…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…The problem is caused by the simple cost function of conventional BME. To solve this problem, adaptive BME that considers the texture of a block was proposed [5]. However, by just considering the texture of the interpolated image, the cost function of this algorithm does not correctly represent the complexity of the original image, which decreases the accuracy of the ME process.…”

Section: Introductionmentioning

confidence: 99%

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Bilateral frame rate upconversion algorithm based on image texture complexity compensation

Lee

2015

Electron. lett.

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A new bilateral frame rate upconversion algorithm using the image texture complexity characteristic is proposed. In the proposed algorithm, as the cost function is adjusted according to the image texture complexity, the accuracy of motion estimation (ME) is improved. In the experimental results, the proposed algorithm outperforms the conventional bilateral ME process by 0.32 dB.Introduction: Frame rate upconversion (FRUC) is an important technology supporting higher temporal resolution. Recently, FRUC has been used to prevent the motion blur problem in liquid crystal displays [1]. In the previous research, motion-compensated frame interpolation (MCFI) has been shown to be an effective scheme for reducing motion judder [2]. Most MCFI algorithms have used the block-matching algorithm (BMA) for motion estimation (ME) because it is simple and easy to implement [3]. Among the several MCFI methods using BMA, bilateral ME (BME) can avoid holes and overlap problems [4]. In conventional BME, a motion vector (MV) is defined based on the temporal symmetry between previous and following frames. However, the BME has a critical weakness when an object with complex texture and a background with homogeneous texture are simultaneously present. The problem is caused by the simple cost function of conventional BME. To solve this problem, adaptive BME that considers the texture of a block was proposed [5]. However, by just considering the texture of the interpolated image, the cost function of this algorithm does not correctly represent the complexity of the original image, which decreases the accuracy of the ME process. In our proposed methods, the texture complexities of the previous and following frames are used simultaneously, considering that a bilateral cost function increases the accuracy of the ME process. It improves the subjective and objective image quality in the interpolated frame. Considering the substantial quality improvement, the resulting increase in computational complexity is negligible.

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Section: Proposed Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bilateral frame rate upconversion algorithm based on image texture complexity compensation

Lee

2015

Electron. lett.

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“…The drawback of this method is its high computational complexity when compared with the traditional method based on the generation of a single MVF. The BME method proposed by [12] works at correcting the MV outliers in the texture region, and the better results on interpolated quality and computational complexity are obtained. The study of scan order in full search and the pipelining of MV post-processing are presented in [13] to improve the accuracy of BME.…”

Section: Introductionmentioning

confidence: 99%

Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation for Frame Rate Up-Conversion

Liu

Chen

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYThe conventional bilateral motion estimation (BME) for motion-compensated frame rate up-conversion (MC-FRUC) can avoid the problem of overlapped areas and holes but usually results in lots of inaccurate motion vectors (MVs) since 1) the MV of an object between the previous and following frames is more likely to have no temporal symmetry with respect to the target block of the interpolated frame and 2) the repetitive patterns existing in video frame lead to the problem of mismatch due to the lack of the interpolated block. In this paper, a new BME algorithm with a low computational complexity is proposed to resolve the above problems. The proposed algorithm incorporates multi-resolution search into BME, since it can easily utilize the MV consistency between two adjacent pyramid levels and spatial neighboring MVs to correct the inaccurate MVs resulting from no temporal symmetry while guaranteeing low computational cost. Besides, the multi-resolution search uses the fast wavelet transform to construct the wavelet pyramid, which not only can guarantee low computational complexity but also can reserve the high-frequency components of image at each level while sub-sampling. The high-frequency components are used to regularize the traditional block matching criterion for reducing the probability of mismatch in BME. Experiments show that the proposed algorithm can significantly improve both the objective and subjective quality of the interpolated frame with low computational complexity, and provide the better performance than the existing BME algorithms.

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Frame Interpolation Algorithm Using Improved 3-D Recursive Search

Xie

Wang

Xiao

et al. 2018

Pattern Recognition and Computer Vision

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Frame rate up-conversion method based on texture adaptive bilateral motion estimation

Cited by 6 publications

References 12 publications

Bilateral frame rate upconversion algorithm based on image texture complexity compensation

Bilateral frame rate upconversion algorithm based on image texture complexity compensation

Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation for Frame Rate Up-Conversion

Frame Interpolation Algorithm Using Improved 3-D Recursive Search

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