A Comprehensive Review of Traditional Video Processing

Joy, Helen K.; Kounte, Manjunath R

doi:10.25046/aj050633

Cited by 5 publications

(1 citation statement)

References 30 publications

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“…When it comes to video, quality is an important parameter. The codecs should have a compression procedure that produces better quality output with less computational cos, considering recent video codec like H.264 [1], H.265(HEVC) [2], H.266 [3]. Versatile video coding (VCC) the issue facing is computational complexity, compression artifact, low coding efficiency etc., the total compression procedure when split into blocks the 70% of compression happens in the initial stage i.e., prediction stage.…”

Section: Introductionmentioning

confidence: 99%

Modelling of Depth Prediction Algorithm for Intra Prediction Complexity Reduction

Joy¹,

Kounte²

2022

ATAIML

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Video compression gained its relevance with the boon of the internet, mobile phones, variable resolution acquisition device etc. The redundant information is explored in initial stages of compression that’s is prediction. Inter prediction that is prediction within the frame generates high computational complexity when working with traditional signal processing procedures. The paper proposes the design of a deep convolutional neural network model to perform inter prediction by crossing out the flaws in the traditional method. It briefs the modeling of network, mathematics behind each stage and evaluation of the proposed model with sample dataset. The video frame’s coding tree unit (CTU) of 64x64 is the input, the model converts and store it as a 16-element vector with the goodness of CNN network. It gives an overview of deep depth decision algorithm. The evaluation process shows that the model performs better for compression with less computational complexity.

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Section: Introductionmentioning

confidence: 99%