Adaptive search pattern for fast motion estimation in HD video

Arnaudov, Pavel; Ogunfunmi, Tokunbo

doi:10.1109/acssc.2017.8335161

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Every "I" frame is taught a new pattern. It has emerged from the findings that the Adaptive Search Pattern makes around 10% -70% of the PSNR difference between current fixed and complete search algorithms [16].…”

Section: The Fuzzy Logic Based Fourmentioning

confidence: 99%

Fuzzy based Search in Motion Estimation for Real Time Video Compression

Srivastava¹,

Kumar²

2021

IJACSA

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Video compression ratio, quality and efficiency are determined by the motion estimation algorithm. Motion estimation is used to perform inter frame prediction in video sequences. The individual frames are divided into blocks the motion estimation is computed by a video codec such as H.264. A video codec computes the displacement of block between the previous frame (reference frame) and the current frame, for each block in current frame the best motion vector is determined in the reference frame as a block belongs to a current frame. In this, research paper, a novel technique has been presented for motion vector calculation, using fuzzy Gaussian membership function. The motion estimation block uses fuzzy membership function to estimate the connectedness of different blocks of the current frame to that of the reference frame The fuzzy decision matching is done based on the matching criterion and the best matching block is selected. The motion vectors are thus calculated with respect to the reference frame. The fuzzification process produces optimally matched blocks, which are then utilized to calculate the motion vectors of the predicted frame. Using fuzzy based search the search area is automatically updated and adaptive search steps provides an optimized result of search. As in real time streaming no file is exchanged during the transmission user is not able to download the file the only way for smooth transmission is frame management fuzzy based search for the motion estimation provides a better compression for the predicted frames.

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Section: The Fuzzy Logic Based Fourmentioning

confidence: 99%

Fuzzy based Search in Motion Estimation for Real Time Video Compression

Srivastava¹,

Kumar²

2021

IJACSA

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“…We have also recently developed several signature based algorithms that attempt to view the frame as a whole and target Full Search quality, while attempting to keep processing times, storage and computation low [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Dynamically Adaptive Fast Motion Estimation Algorithm for HD Video

Arnaudov

Ogunfunmi

2020

J Sign Process Syst

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This paper presents a novel adaptive Fast Motion Estimation (FME) Algorithm, which reduces the number of search points, computational complexity and therefore lowering power consumption, while providing improved quality per watt in FME. The algorithm minimizes computation and storage and from there, power consumption, while trying to preserve quality as much as possible. It is very suitable for hardware implementation, as in a motion co-processor. The pervasiveness of mobile devices with HD video capabilities demands such low power hardware accelerators. The proposed algorithm is a novel method, that can identify the best search pattern within a given region of the HD video frame, based on its motion dynamics to achieve lower power video encoding. The goal is to achieve the best quality with the minimum number of search iterations. The reduced number of checks translates into power savings. The motivation of the presented algorithm is to learn the motion dynamics within a region from a small subset of blocks within that region and apply that knowledge to the remaining large set of blocks in the same region. This adaptiveness makes it robust with respect to the nature of the video. Thus it works equally well with more dynamic and with less dynamic video sequences. The results show that the proposed algorithm can reduce computations by about 4 times compared to other fixed search patterns algorithms, while staying within 1 dB of PSNR results. That equates to about 75% power savings at the expense of not more than 1 dB of PSNR quality loss.

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Raster Search Resolution Analysis for Fast Motion Estimation in HD Video Compression

Arnaudov

Ogunfunmi

2018

2018 IEEE International Workshop on Signal Processing Systems (SiPS)

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Adaptive search pattern for fast motion estimation in HD video

Cited by 3 publications

References 12 publications

Fuzzy based Search in Motion Estimation for Real Time Video Compression

Fuzzy based Search in Motion Estimation for Real Time Video Compression

Dynamically Adaptive Fast Motion Estimation Algorithm for HD Video

Raster Search Resolution Analysis for Fast Motion Estimation in HD Video Compression

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