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首页> 外文期刊>International Journal of Image and Graphics >Improved Listless Embedded Block Partitioning Algorithms for Image Compression
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Improved Listless Embedded Block Partitioning Algorithms for Image Compression

机译:改进的无列表嵌入式块划分算法,用于图像压缩

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摘要

In this paper, two simple yet efficient embedded block-based image compression algorithms are presented. These algorithms not only improve the rate distortion performances of set partitioning in hierarchical trees (SPIHT) and set partitioning in embedded block coder (SPECK) at lower bit rates but also reduces the dynamic memory requirement by 91.1% in comparison to SPIHT. The former objective is achieved by better exploiting the coefficient decaying spectrum of the wavelet transformd images and the later objective is realised by improved listless implementation of the algorithms. The proposed algorithms explicitly perform breadth first search like SPECK. Extensive simulation conducted on various standard grayscale and color images indicate significant peak-signal-to-noise-ratio (PSNR) improvement over most of the state-of-the-art wavelet-based embedded coders including JPEG2000 at lower rates. The reduction of encoding and decoding time as well as improvement in coding efficiency at lower bit rates facilitate these coder as better candidates for multimedia applications.
机译:在本文中,提出了两种简单而有效的基于嵌入式块的图像压缩算法。这些算法不仅以较低的比特率提高了分层树(SPIHT)中的集划分和嵌入式块编码器(SPECK)中的集划分的速率失真性能,而且与SPIHT相比,将动态内存需求降低了91.1%。前一个目的是通过更好地利用小波变换图像的系数衰减谱来实现的,后一个目的是通过改进算法的无精打采实现来实现的。所提出的算法明确执行广度优先搜索,例如SPECK。在各种标准灰度和彩色图像上进行的广泛仿真表明,与大多数最新的基于小波的嵌入式编码器(包括JPEG2000)相比,低信噪比下的峰值信噪比(PSNR)有了显着提高。编码和解码时间的减少以及较低比特率下编码效率的提高促进了这些编码器成为多媒体应用程序的更好候选者。

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