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Ant weight-lifting algorithm for motion estimation

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Abstract

Every video coding standard includes and requires motion estimation and compensation. The full search algorithm, which provides the best motion estimation, has a very high computation cost. Researchers have developed several algorithms to reduce the cost of computation. However, most of these algorithms become trapped in local minima during the search. Population-based evolutionary algorithms are widely used to develop a computationally efficient and cost-effective motion estimation strategy. The most recent effort used the Jaya algorithm to develop a motion estimation process that outperformed the state-of-the-art test zone search algorithm. In this study, a motion estimation algorithm based on the ant weight-lifting approach is proposed. Previously, the ant weight-lifting algorithm was used to solve a variety of problems, such as image segmentation, signal compression, and so on. The ant weight-lifting algorithm's computation cost was reduced by adopting a fitness estimation method that uses nearest-neighbor interpolation and an early termination strategy. Compared to Jaya algorithm-based motion estimation, the proposed algorithm executes up to 3% more quickly and exhibits up to 1.2 dB less distortion.

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Data availability

The test video sequences used during the current study are available in the “YUV Dataset: **ph.org Video Test Media [Derf’s Collection]” repository, https://media.xiph.org/video/derf.

Abbreviations

VVC:

Versatile video coding

GOP:

Group of pictures

TZS:

Test zone search

AWL Algorithm:

Ant weight-lifting algorithm

JABM:

Jaya algorithm-based motion estimation

ZMP:

Zero-motion prejudgment

SAD:

Sum of absolute difference

NNI:

Nearest-neighbor interpolation

PSNR:

Peak signal-to-noise ratio

SSIM:

Structure similarity index metric

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Authors and Affiliations

  1. Department of ETCE, Jadavpur University, Kolkata, 700032, India

    Suvojit Acharjee & Sheli Sinha Chaudhuri

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  1. Suvojit Acharjee
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SA has carried out the research work. Prof. SS Chaudhuri has supervised the research work. Both of them has reviewed the manuscript.

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Correspondence to Suvojit Acharjee.

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Acharjee, S., Chaudhuri, S.S. Ant weight-lifting algorithm for motion estimation. Iran J Comput Sci 6, 207–219 (2023). https://doi.org/10.1007/s42044-022-00134-5

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