Fast motion estimation algorithm based on geometric wavelet transform

Author:

Cheriet Leyla1,Chenikher Salah2,Boukari Karima1

Affiliation:

1. Electronics Department, Badji Mokhtar University of Annaba, Algeria

2. LABGET Laboratory, Department of Electrical Engineering, Larbi Tebessi University of Tebessa, 12000 Tebessa, Algeria

Abstract

Motion estimation is a means, which consists in studying the displacement of objects in a video sequence, seeking the correlation between two successive frames, to predict the change in the contents position. Motion estimation is becoming a progressively significant requirement in a variety of applications such as medicine, robotics and video compression. In recent years, wavelets are effective tools for motion estimation, but the DWT (Discrete Wavelet Transform) will suffer from problems like translation sensitivity, poor directionality and absence of phase information. These three disadvantages make classical wavelets incapable of calculating motion in complex sequences (contain several directions.). In order to improve these negative aspects, we will choose geometric wavelet. Therefore, our objective is to propose a method capable of estimating the motion in terms of performance (speed and accuracy). This method will be based on the geometric wavelet transform and more precisely on the Contourlet transform. This work consists of two parts: in the first stage, the denoising process is examined by the Contourlet transform to ensure the precision of motion; in the second phase, we applied the iterative method of Horn and Schunck to calculate the motion in order to guarantee good speed. Comparative experimental results of artificial sequences show that the proposed algorithm obtains considerably better performance than several state-of-the-art methods.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Information Systems,Signal Processing

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Pedestrian attribute recognition using trainable Gabor wavelets;Heliyon;2021-06

2. IFHS Method on Moving Object Detection in Vehicle Flow;Communications in Computer and Information Science;2020

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