Fractional-pel Interpolation Algorithm Based on Adaptive Filter-Reference-Cited by-同舟云学术

Fractional-pel Interpolation Algorithm Based on Adaptive Filter

Published:2019-11-18 Issue:08 Volume:34 Page:2054022
ISSN:0218-0014
Container-title:International Journal of Pattern Recognition and Artificial Intelligence
language:en
Short-container-title:Int. J. Patt. Recogn. Artif. Intell.

Author:

Wang Gang¹^ORCID,Chen Hexin²,Chen Mianshu¹²,Zhao Qiang¹,Song Yingjie³

Affiliation:

1. School of Mechanical Engineering, Baicheng Normal University, Baicheng 137000, P. R. China

2. College of Communication Engineering, Jilin University, Changchun 130012, P. R. China

3. School of Mechanical and Vehicle Engineering, Changchun University, Changchun 130022, P. R. China

Abstract

In order to further improve fractional-pel interpolation image quality of video sequence with different resolutions and reduce algorithm complexity, the fractional-pel interpolation algorithm based on adaptive filter (AF_FIA) is proposed. This algorithm adaptively selects the interpolation filters with different orders according to the three video sequence regions with different resolutions; in the three video sequence regions with different resolutions, the high-order interpolation filter is replaced by low-order interpolation filter according to the correlation between pixels to realize the adaptive selection of filter. The complexity analysis results show that compared with other algorithms, this algorithm reduces space complexity and computation complexity, thus reducing the storage access and coding time. The simulation results indicate that compared with other algorithms, this algorithm has good coding performance and robustness for video sequences with different resolutions.

Funder

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218001420540221

Reference26 articles.

1. Data-Driven Rate Control for Rate-Distortion Optimization in HEVC Based on Simplified Effective Initial QP Learning

2. High performance loop filter for HEVC

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