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Video Compression with Wavelet Transform Using SPIHT Algorithm in MATLAB Simulink


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1 Rungata College of Engineering and Technology, Bhilai, CG, India
     

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Motion estimation is a common ingredient in many state-of the-art video processing algorithms, serving as an effective way to capture the spatial-temporal correlation in video signals. However, the robustness of motion estimation often suffers from problems such as ambiguities of motion trajectory (i.e. the aperture problem) and illumination variances. In this paper, we explore a new framework for video processing based on the recently proposed wavelet transform with SPIHT algorithm. Instead of containing an explicit motion estimation step, the wavelet transform provides motionselective sub band decomposition for video signals. We demonstrate the potential of this new technique in a video denoising application.

Keywords

Motion Estimation, Spatial, Temporal, Trajectory, Decomposition, Denoising.
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  • Video Compression with Wavelet Transform Using SPIHT Algorithm in MATLAB Simulink

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Authors

Chhabikiran Sao
Rungata College of Engineering and Technology, Bhilai, CG, India
Amit Kolhe
Rungata College of Engineering and Technology, Bhilai, CG, India

Abstract


Motion estimation is a common ingredient in many state-of the-art video processing algorithms, serving as an effective way to capture the spatial-temporal correlation in video signals. However, the robustness of motion estimation often suffers from problems such as ambiguities of motion trajectory (i.e. the aperture problem) and illumination variances. In this paper, we explore a new framework for video processing based on the recently proposed wavelet transform with SPIHT algorithm. Instead of containing an explicit motion estimation step, the wavelet transform provides motionselective sub band decomposition for video signals. We demonstrate the potential of this new technique in a video denoising application.

Keywords


Motion Estimation, Spatial, Temporal, Trajectory, Decomposition, Denoising.