Nearly lossless HDR images compression by background image segmentation

Lei Chen, Zhiming Wang
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引用次数: 3

Abstract

High-Dynamic Rang and high spatial resolutions image, such as 16bits X-ray image, is required in security and medical applications. However, transporting this kind of the image costs a lot in network bandwidth, storage capacity and transmission time. To solve the problem, efficient compression technology is raised. In this paper, we propose a nearly lossless compression algorithm with background segmentation for 16 bits X-ray image. Background and foreground of image are separated with a threshold calculated through detecting background peak of image gray histogram. Background pixels connected to image border are segmented as background by two pass run-length labeling. Then image background is compressed with Run-Length-encoding (RLE) and the foreground is encoded via Lempel-Ziv-77 (LZ77). To validate the proposed algorithm, we compare it with state-of-art compression algorithms LZ77, JPGE_LS, and arithmetic coding. Experimental results show that our algorithm obtains good performance both on compress ratio and speed with neglectable information loss.
基于背景图像分割的近无损HDR图像压缩
在安防和医疗应用中需要高动态距离和高空间分辨率的图像,如16位x射线图像。但是,传输这种图像需要耗费大量的网络带宽、存储容量和传输时间。为了解决这一问题,提出了高效压缩技术。本文提出了一种具有背景分割的16位x射线图像近无损压缩算法。通过检测图像灰度直方图的背景峰值计算阈值,分离图像的背景和前景。连接到图像边界的背景像素通过两次行程长度标记分割为背景。然后用行长编码(RLE)压缩图像背景,用Lempel-Ziv-77 (LZ77)编码前景。为了验证所提出的算法,我们将其与最先进的压缩算法LZ77、JPGE_LS和算术编码进行了比较。实验结果表明,该算法在压缩比和速度上都有较好的性能,且信息损失可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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