具有奇偶降低的近无损图像压缩

B. Koc, Z. Arnavut, S. Voronin, H. Kocak
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引用次数: 1

摘要

在我们之前的工作中,我们介绍了一种基于分层预测、反演和上下文自适应编码技术的无损图像压缩算法(称为BWIC_I)。我们发现,在各种众所周知的图像数据集上,BWIC_I优于最常用的标准彩色图像压缩算法,包括无损模式下的JPEG和JPEG 2000。在本研究中,我们引入了一种近乎无损的图像压缩算法,该算法主要由奇偶降低组成,通过删除RGB彩色图像中像素值的最低有效位,然后使用BWIC_I压缩结果数据。该算法保证了最小的PSNR值。此外,它不需要专门的编码和解码算法,并且可以与其他通用图像压缩算法结合使用。在标准的柯达图像集上证明,该技术的压缩性能明显优于JPEG和JPEG 2000。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-lossless Image Compression with Parity Reduction
In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.
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