Motion vector generation for video coding by gray prediction

---Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression.

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“…Y. -G. Wu and G. -F. Huang [99] proposed motion vector generation using gray theory [100] proposed in 1982. Fig.…”

Section: Search Pattern Used In First Stepmentioning

confidence: 99%

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Kamble¹,

Thakur²,

Bajaj³

2016

IJIMAI

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“…The computing power required to implement these algorithms is illustrated by the fact that only recently have personal computers been able to compress video in real time. A typical mobile device has much fewer computational resources than an ordinary computer [18]. Although custom video compression chipsets are available, they have not yet been included in general technology due to their cost, power, and size limitations [19,20].…”

Section: Introductionmentioning

confidence: 99%

Computer Network Redundancy Reduction Using Video Compression

et al. 2023

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Due to the strong correlation between symmetric frames, video signals have a high degree of temporal redundancy. Motion estimation techniques are computationally expensive and time-consuming processes used in symmetric video compression to reduce temporal redundancy. The block-matching technique is, on the other hand, the most popular and efficient of the different motion estimation and compensation techniques. Motion compensation based on the block-matching technique generally uses the minimization of either the mean square error (MSE) or mean absolute difference (MAD) in order to find the appropriate motion vector. This paper proposes to remove the highly temporally redundant information contained in each block of the video signal using the removing temporal redundancy (RTR) technique in order to improve the data rate and efficiency of the video signal. A comparison between the PSNR values of this technique and those of the JPEG video compression standard is made. As a result of its moderate memory and computation requirements, the algorithm was found to be suitable for mobile networks and embedded devices. Based on a detailed set of testing scenarios and the obtained results, it is evident that the RTR compression technique allowed a compression ratio of 22.71 and 95% loss in bit rate reduction while maintaining sufficient intact signal quality with minimized information loss.

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Fractal Video Compression using Block Matching Motion Estimation - A Study

Aswani¹,

Kamble²

2014

IOSRJVSP

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Motion vector generation for video coding by gray prediction

Cited by 3 publications

References 10 publications

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Computer Network Redundancy Reduction Using Video Compression

Fractal Video Compression using Block Matching Motion Estimation - A Study

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