基于JPEG2000的稀疏直方图图像无损压缩新方法

M. Aguzzi, M. Albanesi
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引用次数: 1

摘要

本文提出了一种新的稀疏直方图图像压缩方法。首先,我们定义了一个稀疏度指标,该指标提示了矩阵稀疏度的数学概念与像素分布的视觉信息之间的关系。我们使用该指数来更好地了解我们的方法的范围及其首选的适用领域,并评估性能。提出了两种改进JPEG2000标准编码步骤的无损图像压缩算法。参考该标准对增益进行了理论研究。对文献中标准化程度较高的图像的实验结果证实了这一期望,特别是对高度稀疏的图像。
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A Novel Approach to Sparse Histogram Image Lossless Compression using JPEG2000
In this paper a novel approach to the compression of sparse histogram images is proposed. First, we define a sparsity index which gives hints on the relationship between the mathematical concept of matrix sparsity and the visual information of pixel distribution. We use this index to better understand the scope of our approach and its preferred field of applicability, and to evaluate the performance. We present two algorithms which modify one of the coding steps of the JPEG2000 standard for lossless image compression. A theoretical study of the gain referring to the standard is given. Experimental results on well standardized images of the literature confirm the expectations, especially for high sparse images.
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Progress in Computer Vision and Image Analysis A Novel Approach to Sparse Histogram Image Lossless Compression using JPEG2000 Architectural Scene Reconstruction from single or Multiple Uncalibrated Images Prior Knowledge Based Motion Model Representation Combining Particle filter and Population-Based Metaheuristics for Visual Articulated Motion Tracking
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