A wavelet based low complexity embedded block coding algorithm

B. Das, S. Banerjee
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引用次数: 0

Abstract

Summary form only given. Along with compression efficiency, other factors, like complexity, are significant issues for image coding. The measure of complexity varies from application to application. To overcome the problems of large database maintenance and the high computational burden of EZT and SPIHT, a new algorithm, WEBLOC (Wavelet-based Embedded BLOck Coding), is proposed for low complexity, near lossless compression. The most significant characteristics of this algorithm involve (a) sign-bit arrangement (b) subband intensity distribution statistics. Results were obtained with monochrome 8 bpp, 256/spl times/256 images. The salient features of the coding algorithm can be summarized as follows. Entropy coding is replaced by fixed RLC (runlength coding), considerably reducing the computational overhead and also the time overhead. For near lossless image compression, the reduction of complexity highly reduces the hardware circuitry. The running memory overhead for any list is reduced as compared to the EZT and SPIHT. However, the memory requirement for storing the wavelet coefficients is not reduced.
一种基于小波的低复杂度嵌入式分组编码算法
只提供摘要形式。除了压缩效率外,其他因素(如复杂性)也是图像编码的重要问题。复杂度的度量因应用程序而异。针对EZT和SPIHT的数据库维护量大、计算量大等问题,提出了一种低复杂度、接近无损压缩的WEBLOC (Wavelet-based Embedded BLOck Coding)算法。该算法最显著的特点包括(a)符号位排列(b)子带强度分布统计。结果获得单色8 bpp, 256/ sp1次/256张图像。编码算法的显著特点可以概括如下。熵编码被固定的RLC(运行长度编码)所取代,大大减少了计算开销和时间开销。对于接近无损的图像压缩,复杂度的降低大大减少了硬件电路。与EZT和SPIHT相比,任何列表的运行内存开销都减少了。然而,存储小波系数的内存需求并没有减少。
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