An Automated Algorithm for Approximation of Temporal Video Data Using Linear B'EZIER Fitting

TL;DR

This paper introduces an automated linear Bezier fitting algorithm for approximating temporal video data, optimizing compression by minimizing segments while maintaining quality, and avoiding blocking artifacts.

Contribution

It presents a novel automated method for fitting temporal video data with linear Bezier curves, improving compression efficiency and quality preservation.

Findings

Effective in lossy video compression

Maintains high subjective and objective quality

Prevents blocking artifacts

Abstract

This paper presents an efficient method for approximation of temporal video data using linear Bezier fitting. For a given sequence of frames, the proposed method estimates the intensity variations of each pixel in temporal dimension using linear Bezier fitting in Euclidean space. Fitting of each segment ensures upper bound of specified mean squared error. Break and fit criteria is employed to minimize the number of segments required to fit the data. The proposed method is well suitable for lossy compression of temporal video data and automates the fitting process of each pixel. Experimental results show that the proposed method yields good results both in terms of objective and subjective quality measurement parameters without causing any blocking artifacts.