• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.55-62
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• 2012

EZW, also known as Embedded Zerotree Wavelet, is a technique that allows transforming original images into wavelet, then again compressing images using the transformed data. This algorithm demonstrates a simple structure and remarkable effectiveness. This paper has reformed the EZW to improve a compression efficiency. Fundamentally, EZW evaluates the priority level of wavelet-transformed data and stores them into four different categories considering the priority level of the data as well as their location information. The four categories are represented as the symbols P, N, Z, and T. Here, P and N correspond to the volume of data and the priority level whereas Z and T show the location information of data. Each letter is stored through the process of dominant pass. However, here is when the data of Z and T are stored redundantly which lead to unnecessary increase of data volume. In this paper, we propose a modified version of Embedded Zerotree Wavelet algorithm, which is designed to efficiently reduce the volume of redundantly stored data using four additionally inserted symbols. We name it EEZW, Extended Embedded Zerotree Wavelet. The proposed algorithm demonstrates the efficiency verified by a number of image and confirms an outstanding result through the PSNR(Peak Signal To Noise Rate) values, which measure their quality of images.