EFFICIENT VIDEO COMPRESSION USING HEVC AND NON-LINEAR CONVOLUTIONAL MOBILEVNET BASED RATE-DISTORTION OPTIMIZATION
Abstract
With the surge in demand for high-quality video content over various platforms, efficient video compression techniques have become indispensable. High-Efficiency Video Coding (HEVC) has been a cornerstone, yet further enhancements are essential for optimal compression. Despite HEVC’s advancements, achieving optimal compression while maintaining video quality remains challenging. Additionally, existing methods often overlook the computational complexity, hindering real-time applications. We propose a novel approach integrating HEVC with Non-Linear Convolutional MobileNet (NLCM) for enhanced compression efficiency. Our method employs a rate-distortion optimization framework, leveraging the capabilities of both HEVC and NLCM to achieve superior compression performance. NLCM provides adaptive filtering, enhancing spatial and temporal correlations, while HEVC ensures high compression efficiency. Through experimentation on standard video datasets, our method demonstrates significant improvements over existing techniques. Compared to HEVC alone, our approach achieves up to 30% reduction in bitrate at equivalent perceptual quality levels. Moreover, computational complexity is reduced by 15%, enabling real- time applications without compromising performance. The proposed method exhibits competitive results across various resolutions and frame rates, making it versatile for diverse video compression scenarios.

Authors
D. Prabakar1, K. Venkata Ramana2, A. Thangam3, S. Esakki Rajavel4, Geogen George5
Karpagam College of Engineering, India1, QIS College of Engineering and Technology, India2, Pondicherry University Community College, India3, Karpagam Academy of Higher Education, India4, University of Technology and Applied Sciences, Sultanate of Oman5

Keywords
HEVC, Non-Linear Convolutional MobileNet, Compression Efficiency, Rate-Distortion Optimization
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Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 14 , Issue: 4 , Pages: 3273 - 3281 )
Date of Publication :
May 2024
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94
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