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A New Bit-Plane Entropy Coder for Scalable Image Coding

机译:一种新的可伸缩图像编码位平面熵编码器

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Compression ratio and computational complexity are two major factors for a successful image coder. By exploring the Laplacian distribution of the wavelet coefficients, a new bit plane entropy coder is proposed in this paper. Compared with the state-of-the-art JPEG2000 entropy coder (EBCOT), the proposed coder achieves a 0.75% better loss less performance for 5 level 5/3 wavelet decomposition at block size 64 £ 64 and 2.56% at block size 16 £ 16. Experimental results also show PSNR improvements of about 0.13dB at 1bpp and 0.25dB at 2bpp on average for lossy compression. However, the gain in coding performance is not based on increasing computational complexity but in stead a reduction by using a static arithmetic coder which avoids complicated adaptive procedure.
机译:压缩率和计算复杂度是成功的图像编码器的两个主要因素。通过探索小波系数的拉普拉斯分布,提出了一种新的位平面熵编码器。与最新的JPEG2000熵编码器(EBCOT)相比,在块大小为64£64的情况下,对于5级5/3小波分解,所提出的编码器实现了0.75%的更好的损失少,而在块大小为16£的情况下,则达到了2.56% 16.实验结果还表明,对于有损压缩,PSNR在1bpp时平均提高约0.13dB,在2bpp时平均提高0.25dB。但是,编码性能的提高不是基于增加的计算复杂度,而是通过使用静态算术编码器来减少,这避免了复杂的自适应过程。

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