FPGA Design of Area Efficient and Superfast Motion Estimation Using JAYA Optimization-Based Block Matching Algorithm

Praveena, M.; Balaji, N.; Naidu, C. D.

doi:10.1007/978-981-19-4990-6_13

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…The JABM outperforms the stateof-the-art TZS. Praveena et al [19] proposed an FPGA design of JABM. This design will not affect the JABM's search speed.…”

Section: Previous Workmentioning

confidence: 99%

Ant weight-lifting algorithm for motion estimation

Acharjee

Chaudhuri

2023

Iran J Comput Sci

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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 e cient 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 tness 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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“…The JABM outperforms the stateof-the-art TZS. Praveena et al [19] proposed an FPGA design of JABM. This design will not affect the JABM's search speed.…”

Section: Previous Workmentioning

confidence: 99%

Ant weight-lifting algorithm for motion estimation

Acharjee

Chaudhuri

2023

Iran J Comput Sci

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A low power arithmetic unit driven motion estimation and intra prediction accelerators with adaptive Golomb–Rice entropy encoder for H.264 encoders on FPGA

Vigneash,

Azath,

Nair

et al. 2024

Analog Integr Circ Sig Process

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Ant Weight Lifting Algorithm for Motion Estimation

Acharjee

Chaudhuri

2023

Preprint

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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.

show abstract

FPGA Design of Area Efficient and Superfast Motion Estimation Using JAYA Optimization-Based Block Matching Algorithm

Cited by 3 publications

References 26 publications

Ant weight-lifting algorithm for motion estimation

Ant weight-lifting algorithm for motion estimation

A low power arithmetic unit driven motion estimation and intra prediction accelerators with adaptive Golomb–Rice entropy encoder for H.264 encoders on FPGA

Ant Weight Lifting Algorithm for Motion Estimation

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