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Regional Partitioned Iterated Function Systems for digital image enhancement

机译:用于数字图像增强的区域分区迭代功能系统

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摘要

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.
机译:提出了一种用于增强数字图像对比度的新技术。所提出的方法基于分区迭代功能系统(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多个区域。每个域区域进一步划分为较小范围的区域。依次地,通过收缩仿射空间变换以及通过其像素的灰度级的线性变换来变换每个范围区域。在处理每个区域之后,使用PIFS来创建原始图像的低通版本。对比度增强的图像是通过将原始图像与其低通版本的差异添加到原始图像本身而获得的。获得的定量和定性结果表明,与两种广泛使用的对比度增强技术相比,该方法可实现更高质量的图像增强。

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