Image zooming using directional cubic convolution interpolation

Zhou, Dengwen; Shen, Xiao Liu; Dong, Weiming

doi:10.1049/iet-ipr.2011.0534

Cited by 113 publications

(86 citation statements)

References 15 publications

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“…The most edge-directed interpolation algorithms [3][4][5][6][7][8][9][10][11] including the proposed TEI method can successfully enlarge the low-resolution images to super-resolution ones with less artifacts along the texture edges. However, the loss of high-frequency components cannot be properly restored by general interpolation algorithms.…”

Section: Image Enhancement and Dithering Algorithmsmentioning

confidence: 99%

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An iterative enhanced super-resolution system with edge-dominated interpolation and adaptive enhancements

Lin

Yang

et al. 2015

EURASIP J. Adv. Signal Process.

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For super-resolution (4K × 2K) displays, super-resolution technologies, which can upsample videos to higher resolution and achieve better visual quality, become more and more important currently. In this paper, an iterative enhanced super-resolution (IESR) system which is based on two-pass edge-dominated interpolation, adaptive enhancement, and adaptive dithering techniques is proposed. The two-pass edge-dominated interpolation with a simple and regular kernel can sharpen visual quality while the adaptive enhancement can provide high-frequency perfection and the adaptive dithering conveys naturalization enhancement such that the proposed IESR system achieves better peak signal-to-noise ratio (PSNR) and exhibits better visual quality. Experimental results indicate that the proposed IESR system, which improves PSNR up to 28.748 dB and promotes structural similarity index measurement (SSIM) up to 0.917611 in averages, is better than the other existing methods. Simulations also exhibit that the proposed IESR system acquires lower computational complexity than the methods which achieve similar visual quality.

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Section: Image Enhancement and Dithering Algorithmsmentioning

confidence: 99%

“…The linear, bi-cubic, and cubic spline interpolations [2] are the possible means for reducing the complexity. To prevent filtering pixels across edges, numerous edge-directed interpolation methods are proposed [3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

An iterative enhanced super-resolution system with edge-dominated interpolation and adaptive enhancements

Lin

Yang

et al. 2015

EURASIP J. Adv. Signal Process.

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“…Many interpolation methods, including adaptive and non-adaptive methods, have been proposed in the last several decades. Classical non-adaptive methods, such as linear and cubic convolution methods [2] are preferable because of their computational simplicity, however, these methods are unable to adapt with varying local structures of a LR image, which causes undesirable artifacts such as blurring, blocking, and ringing around edges [3]. Several adaptive interpolation methods [2,[4][5][6][7][8][9][10][11][12][13][14][15], including edge-directed methods, have been proposed to address the problems of the aforementioned algorithms and to improve the perceptual quality of the interpolated images.…”

Section: Introductionmentioning

confidence: 99%

Improved image magnification algorithm based on Otsu thresholding

Harb

Isa

Salamah

2015

Computers & Electrical Engineering

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“…Some bicubic-improved approaches based on edge direction detection [6,7] have emerged in recent years, these can produce high quality real-time magnified images for digital TV. To repair missing pixels, Zhou et al [6] explicitly judge the local edge direction according to the gradient radio in two orthogonal directions. Bicubic interpolation along the edge direction is then used for the pixel on a strong edge.…”

Section: Introductionmentioning

confidence: 99%

A novel adaptive image zooming scheme via weighted least-squares estimation

Zhong

Feng

Wang

et al. 2015

Front. Comput. Sci.

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A critical issue in image interpolation is preserving edge detail and texture information in images when zooming. In this paper, we propose a novel adaptive image zooming algorithm using weighted least-square estimation that can achieve arbitrary integer-ratio zoom (WLS-AIZ) For a given zooming ratio n, every pixel in a low-resolution (LR) image is associated with an n × n block of high-resolution (HR) pixels in the HR image. In WLS-AIZ, the LR image is interpolated using the bilinear method in advance. Model parameters of every n×n block are worked out through weighted least-square estimation. Subsequently, each pixel in the n × n block is substituted by a combination of its eight neighboring HR pixels using estimated parameters. Finally, a refinement strategy is adopted to obtain the ultimate HR pixel values. The proposed algorithm has significant adaptability to local image structure. Extensive experiments comparing WLS-AIZ with other state of the art image zooming methods demonstrate the superiority of WLS-AIZ. In terms of peak signal to noise ratio (PSNR), structural similarity index (SSIM) and feature similarity index (FSIM), WLS-AIZ produces better results than all other image integer-ratio zoom algorithms.

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Image zooming using directional cubic convolution interpolation

Cited by 113 publications

References 15 publications

An iterative enhanced super-resolution system with edge-dominated interpolation and adaptive enhancements

An iterative enhanced super-resolution system with edge-dominated interpolation and adaptive enhancements

Improved image magnification algorithm based on Otsu thresholding

A novel adaptive image zooming scheme via weighted least-squares estimation

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