基于视觉注意力的自适应彩色图像压缩

N. Ouerhani, J. Bracamonte, Heinz Hugli, M. Ansorge, F. Pellandini
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引用次数: 51

摘要

本文报道了一种自适应静态彩色图像压缩方法,该方法可以产生相对于输入图像的其余部分具有更高重建质量的自动选择感兴趣区域。ROI是基于视觉注意力的纯数据驱动技术动态生成的。受生物视觉的启发,多重视觉注意算法检测图像中视觉上最显著的区域。因此,当在具有低比特率约束的系统中运行时,自适应编码方案倾向于将更高数量的比特分配给那些对人类视觉系统更明显的图像区域。这种自适应方法产生的压缩图像文件与JPEG标准完全兼容,有利于其广泛应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive color image compression based on visual attention
This paper reports an adaptive still color image compression method which produces automatically selected ROI with a higher reconstruction quality with respect to the rest of the input image. The ROI are generated on-the fly with a purely data-driven technique based on visual attention. Inspired from biological vision, the multicue visual attention algorithm detects the most visually salient regions of an image. Thus, when operating in systems with low bit rate constraints, the adaptive coding scheme favors the allocation of a higher number of bits to those image regions that are more conspicuous to the human visual system. The compressed image files produced by this adaptive method are fully compatible with the JPEG standard, which favors their widespread utilization.
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