数字图像增强的区域划分迭代函数系统

T. Economopoulos, P. Asvestas, G. Matsopoulos
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引用次数: 0

摘要

提出了一种增强数字图像对比度的新技术。该方法基于分区迭代函数系统(PIFS)算法的区域应用。使用标准的区域增长方法将主题图像划分为域区域。每个域区域进一步划分为更小的范围区域。然后,通过压缩仿射空间变换变换每个范围区域,以及通过其像素的灰度级的线性变换。使用PIFS是为了在处理每个区域后创建原始图像的低通版本。对比度增强图像是将原图像与低通图像的差值加到原图像上得到的。定量和定性结果表明,与两种常用的对比度增强技术相比,该方法实现了更高质量的图像增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Regional Partitioned Iterated Function Systems for digital image enhancement
A new technique is presented for enhancing the contrast of digital images. The proposed method is based on the regional application of the Partitioned Iterated Function Systems (PIFS) algorithm. The subject image is partitioned into domain regions, using a standard Region Growing approach. Each domain region is further partitioned into smaller range regions. In turn, each range region is transformed through a contractive affine spatial transform, as well as through a linear transform of the gray levels of its pixels. The PIFS is used in order to create a lowpass version of the original image, after processing each region. The contrast-enhanced image is obtained by adding the difference of the original image with its lowpass version, to the original image itself. The quantitative and qualitative results obtained, show that the proposed method achieves higher quality image enhancement, compared to two widely used contrast enhancement techniques.
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