计算机视觉
人工智能
计算机科学
图像增强
图像(数学)
红外线的
模式识别(心理学)
光学
物理
作者
Seungyoun Lee,Daeyeong Kim,Changick Kim
标识
DOI:10.1109/lsp.2018.2834429
摘要
A novel image enhancement method for infrared (IR) images is presented. The proposed method consists of two parts considering the characteristics of high-dynamic-range IR images. First, we attempt to enhance image contrast by introducing the ramp distribution that increases with a constant slope in an ordered histogram domain. The ramp-distributed histogram is incorporated into an optimization problem with a sorted histogram of the input image to calculate a modified histogram. Second, to deal with blurred effects on IR images, we propose a relative edge-strength index for high-boost filtering to effectively suppress noise in relatively uniform regions. Compared with various conventional and state-of-the-art algorithms, the proposed method shows highly competitive performance.
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