Background and Literature Survey

Chakrabarti, Indrajit; Batta, Kota Naga Srinivasarao; Chatterjee, Sumit Kumar

doi:10.1007/978-3-319-14376-7_2

Cited by 1 publication

(1 citation statement)

References 39 publications

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“…Due to the fact that all of the search candidates are assessed in full search, based on full search, Motion Estimation yields the optimal solution [6]. Even though a full search provides explicit results, it needs a large amount of computation [7].…”

Section: Normal Full Search Algorithm (Nfs)mentioning

confidence: 99%

Utilizing Motion Direction of Video Capturing Satellites for Complexity Reduction in Video Compressor Block-Matching Techniques

Bayat,

Rongke,

Zarrini

2024

Preprint

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This paper aims to define how to combine satellite motion direction in Video Compressor Block-Matching algorithms. In this study, three objectives were identified: unveiling the existence of the problem by evidence-gathering, proposing a preliminary satellite design for video-capturing missions, and using the motion pattern of a satellite. To satisfy the first research objective, videos of Earth and other celestial bodies were selected, and the validity of this claim was evaluated. The alignment of the direction of satellite motion with the motion vectors can be clearly recognized. In all cases, except for one case, the motion vectors of the selected videos were shown to be more than 80%. Investigations determined that the review of the divisions of the Regions and appropriate selection of the boundaries of the Regions can produce more acceptable results for the video whose dominated motion vectors are divided into two different Regions. To satisfy the second objective, which is defined as creating the necessary changes in the design of satellites that have the mission of capturing videos of the celestial bodies, a conceptual design was presented in which the path of receiving the motion directions from the satellite platform to the payload was specified. Here, two modes were proposed: Normal and Proposed. In future rounds, this information can be used to reduce the amount of motion estimation calculations and complexity.

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Section: Normal Full Search Algorithm (Nfs)mentioning

confidence: 99%