What is it about?
This work focuses on making digital images smaller in file size without noticeably reducing their quality. The method improves an existing image compression technique called EZW (Embedded Zerotree Wavelet coding), which is commonly used in wavelet-based image processing. In simple terms, the proposed approach helps store and transmit images more efficiently by reducing unnecessary data while preserving important visual details. The modified method is designed to achieve better compression performance, faster processing, or improved image quality compared to the conventional EZW technique.
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Why is it important?
This work is important because it improves image compression, allowing digital images to use less storage space and bandwidth while maintaining good quality. This helps in faster transmission, efficient storage, and better performance in applications such as multimedia, medical imaging, and online communication.
Perspectives
This work represents an effort to improve the efficiency of digital image compression by enhancing the traditional EZW wavelet coding technique. The motivation behind this study was to explore how image data can be represented more effectively while preserving visual quality. Through the proposed modifications, the work aims to achieve better compression performance and contribute toward faster and more efficient image storage and transmission.
Sanjeev Ghosh
Thakur College of Engineering and Technology
Read the Original
This page is a summary of: Modified EZW, a wavelet coder, February 2011, ACM (Association for Computing Machinery),
DOI: 10.1145/1980022.1980040.
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