Image Compression Using New Entropy Coder

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Digital images contain large amount of information that need evolving effective techniques for storing and transmitting the ever increasing volumes of data. Image compression addresses the problem by reducing the amount of data required to represent a digital image. Image compression is achieved by removing data redundancy while preserving information content. In this paper, a simplified and more effective version of the RUN-Length coder is described and implemented. The proposed algorithm works on quantized coefficients of the Discrete Cosine Transform (DCT) where there are a lot of coincident tokens. Experimental results show that the new approach attains competitive performance.