An Edge Dependent Weighted Filter for Video Deinterlacing

Hao ZHANG; Mengtian RONG; Tao LIU

doi:10.1587/transfun.E98.A.788

An Edge Dependent Weighted Filter for Video Deinterlacing

Hao ZHANG, Mengtian RONG, Tao LIU

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In this letter, we propose a new intra-field deinterlacing algorithm based on an edge dependent weighted filter (EDWF). The proposed algorithm consists of three steps: 1) calculating the gradients of three directions (45°, 90°, and 135°) in the local working window; 2) achieving the weights of the neighboring pixels by exploiting the edge information in the pixel gradients; 3) interpolating the missing pixel using the proposed EDWF interpolator. Compared with existing deinterlacing methods on different images and video sequences, the proposed algorithm improves the peak signal-to-noise-ratio (PSNR) while achieving better subjective quality.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E98-A No.2 pp.788-791

Publication Date: 2015/02/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E98.A.788

Type of Manuscript: LETTER

Category: Image

Authors

Hao ZHANG
  Shanghai Jiao Tong University
Mengtian RONG
  Shanghai Jiao Tong University
Tao LIU
  Shanghai Jiao Tong University

Keyword

deinterlacing, edge dependent weighted filter, image quality

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Hao ZHANG, Mengtian RONG, Tao LIU, "An Edge Dependent Weighted Filter for Video Deinterlacing" in IEICE TRANSACTIONS on Fundamentals, vol. E98-A, no. 2, pp. 788-791, February 2015, doi: 10.1587/transfun.E98.A.788.
Abstract: In this letter, we propose a new intra-field deinterlacing algorithm based on an edge dependent weighted filter (EDWF). The proposed algorithm consists of three steps: 1) calculating the gradients of three directions (45°, 90°, and 135°) in the local working window; 2) achieving the weights of the neighboring pixels by exploiting the edge information in the pixel gradients; 3) interpolating the missing pixel using the proposed EDWF interpolator. Compared with existing deinterlacing methods on different images and video sequences, the proposed algorithm improves the peak signal-to-noise-ratio (PSNR) while achieving better subjective quality.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E98.A.788/_p

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@ARTICLE{e98-a_2_788,
author={Hao ZHANG, Mengtian RONG, Tao LIU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Edge Dependent Weighted Filter for Video Deinterlacing},
year={2015},
volume={E98-A},
number={2},
pages={788-791},
abstract={In this letter, we propose a new intra-field deinterlacing algorithm based on an edge dependent weighted filter (EDWF). The proposed algorithm consists of three steps: 1) calculating the gradients of three directions (45°, 90°, and 135°) in the local working window; 2) achieving the weights of the neighboring pixels by exploiting the edge information in the pixel gradients; 3) interpolating the missing pixel using the proposed EDWF interpolator. Compared with existing deinterlacing methods on different images and video sequences, the proposed algorithm improves the peak signal-to-noise-ratio (PSNR) while achieving better subjective quality.},
keywords={},
doi={10.1587/transfun.E98.A.788},
ISSN={1745-1337},
month={February},}

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TY - JOUR
TI - An Edge Dependent Weighted Filter for Video Deinterlacing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 788
EP - 791
AU - Hao ZHANG
AU - Mengtian RONG
AU - Tao LIU
PY - 2015
DO - 10.1587/transfun.E98.A.788
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E98-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2015
AB - In this letter, we propose a new intra-field deinterlacing algorithm based on an edge dependent weighted filter (EDWF). The proposed algorithm consists of three steps: 1) calculating the gradients of three directions (45°, 90°, and 135°) in the local working window; 2) achieving the weights of the neighboring pixels by exploiting the edge information in the pixel gradients; 3) interpolating the missing pixel using the proposed EDWF interpolator. Compared with existing deinterlacing methods on different images and video sequences, the proposed algorithm improves the peak signal-to-noise-ratio (PSNR) while achieving better subjective quality.
ER -