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The "Joint Data-Hiding and Compression Scheme Based on Side Match Vector Quantization and Image Inpainting" is an innovative approach that integrates data hiding, compression, and image restoration techniques. The scheme utilizes side-match vector quantization (SMVQ) for efficient data compression, where vectors of data are compressed by exploiting similarities between neighboring data points. Simultaneously, it hides secret information within the compressed data. The image inpainting technique is then employed to restore missing parts or add subtle distortions to the image, ensuring that the…mehr

Produktbeschreibung
The "Joint Data-Hiding and Compression Scheme Based on Side Match Vector Quantization and Image Inpainting" is an innovative approach that integrates data hiding, compression, and image restoration techniques. The scheme utilizes side-match vector quantization (SMVQ) for efficient data compression, where vectors of data are compressed by exploiting similarities between neighboring data points. Simultaneously, it hides secret information within the compressed data. The image inpainting technique is then employed to restore missing parts or add subtle distortions to the image, ensuring that the hidden data is well-integrated into the image while maintaining visual quality. This method aims to enhance security and compression efficiency in multimedia systems.
Autorenporträt
This is Dr. Arjun Nichal working as an Associate Professor in the Adarsh Institute of Technology and Research Centre, Vita, Maharashtra, India. Published papers in international journals and conferences. Filled, published, and granted patents. sharing knowledge through blogs and YouTube channels.