Karali A Onur, Okman O Erman, Aytaç Tayfun
TUBITAK UEKAE-ILTAREN, Sehit Yzb. Ilhan Tan Kişlasi, 8 cad., 417 sok., TR-06800 Umitköy, Ankara, Turkey.
J Opt Soc Am A Opt Image Sci Vis. 2010 Mar 1;27(3):509-17. doi: 10.1364/JOSAA.27.000509.
Image enhancement is an important preprocessing step of infrared (IR) based target recognition and surveillance systems. For a better visualization of targets, it is vital to develop image enhancement techniques that increase the contrast between the target and background and emphasize the regions in the target while suppressing noises and background clutter. This study proposes what we believe to be a novel IR image enhancement method for sea-surface targets based on local frequency cues. The image is transformed blockwise into the Fourier domain, and clustering is done according to the number of expected regions to be enhanced in the scene. Based on the variations in the elements in any cluster and the differences between the cluster centers in the frequency domain, two gain matrices are computed for midfrequency and high frequency images by which the image is enhanced accordingly. We provide results for real data and compare the performance of the proposed algorithm through subjective and quantitative tests with four different enhancement methods. The algorithm shows a better performance in the detail visibility of the target.
图像增强是基于红外（IR）的目标识别和监视系统的重要预处理步骤。为了更好地可视化目标，开发能够增加目标与背景之间的对比度、突出目标区域同时抑制噪声和背景杂波的图像增强技术至关重要。本研究提出了一种我们认为基于局部频率线索的用于海面目标的新型红外图像增强方法。图像按块变换到傅里叶域，并根据场景中预期增强区域的数量进行聚类。基于任何聚类中元素的变化以及频域中聚类中心之间的差异，为中频和高频图像计算两个增益矩阵，并据此对图像进行增强。我们给出了真实数据的结果，并通过与四种不同增强方法的主观和定量测试来比较所提算法的性能。该算法在目标细节可见性方面表现出更好的性能。
