Embedded ZeroBlock Coding and context modeling (EZBC) algorithm has high compression performance. However, it consumes large amounts of memory space because an Amplitude Quadtree of wavelet coefficients and other two link lists would be built during the encoding process. This is one of the big challenges for EZBC to be used in real time or hardware applications. An improved EZBC algorithm based on bit length of coefficients was brought forward in this article. It uses Bit Length Quadtree to complete the coding process and output the context for Arithmetic Coder. It can achieve the same compression performance as EZBC and save more than 75% memory space required in the encoding process. As Bit Length Quadtree can quickly locate the wavelet coefficients and judge their significance, the improved algorithm can dramatically accelerate the encoding speed. These improvements are also beneficial for hardware. PACS: 42.30.Va, 42.30.Wb

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An improved EZBC algorithm based on block bit length

We present an efficient implementation of the Embedded Zeroblock Coding (EZBC) algorithm for image compression called Listless EZBC (LSEZBC) The LSEZBC implementation avoids the high computation and memory costs due to the use of link-lists in EZBC by using fixed-size state buffers to keep track of the set partitionings and coding process Large groups of predictable coefficients are efficiently skipped during the coding process by using a recursive scanning method The new implementation requires less memory and lower complexity than EZBC but has similar performance Moreover, LSEZBC is extended for shape-adaptive coding Superior performance is demonstrated when compared with several prominent shape-adaptive coders

Embedded Zeroblock Coding of images without lists

Today digital imaging is widely used in every application around us like Internet, High Definition TeleVision (HDTV), satellite communications, fax transmission, and digital storage of movies and more, because it provide superior resolution and quality. Recently, medical imaging has begun to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. However, medical imaging requires storing, communicating and manipulating large amounts of digital data. Applying image compression reduces the storage requirements, network traffic, and therefore improves efficiency. This chapter provides the need for medical image compression; different approaches to image compression, emerging wavelet based lossy-lossless compression techniques, how the existing recent compression techniques work and also comparison of results. After completing this chapter, the reader should have an idea of how to increase the compression ratio and at the same time maintain the PSNR level compared to the existing techniques, desirable features of standard compression techniques such as embededness and progressive transmission, how these are very useful and much needed in the interactive teleradiology, telemedicine and telebrowsing applications.

Survey of Medical Image Compression Techniques and Comparative Analysis

Among bit plane coding field, coding of significance layer is an important topic. According to the advantage of quad-tree representation on codeword reduction for large zero blocks, zero block coding is a potential method in significance coding. However, traditional embedded zero block coding method exhibits repeated node visits in recursive procedure calling. In this paper, a top-to-button significance coding methodology is proposed to reduce the repeated node visiting. On the other hand, the produced coefficients are reduced at the same time. According to the experiment results, the visited node count and transmitted codeword of proposed work is smaller than original embedded zero block coding and the significance layer in Wavelet transformed coefficients of JPEG 2000. Besides, the reduction of node visiting count increases the significant bit updating efficiency. The results prove the efficiency and the effectiveness of codeword reduction of proposed work.

A Fast and Effective Algorithm for Significance Coding Using Zero Block Coding Technology

In this paper, an improved algorithm based on EZBC and its implementation architecture with low complexity and high performance are presented. The proposed algorithm utilizes the significance state table of quadtree nodes and the context look-up table to control the coding passes and form the context, so the proposed algorithm requires low memory and has low implementation complexity with the nearly same performance.

Improved EZBC algorithm with low complexity

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Improved EZBC algorithm with low complexity