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Cepstrum adaptive plateau histogram for dark IR night vision images enhancement

机译:黑暗IR夜视图像增强的综衣自适应高原直方图

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摘要

This paper presents a novel enhancement algorithm for infrared (IR) images. This suggested algorithm mixes the benefits of the adaptive plateau histogram equalization (APH) and the cepstrum of homomorphic filtering enhancement (CHFE). The main idea of this approach depends on applying the APH on the IR image. Then, the resultant image is applied on the frequency domain by using the CHFE. This CHFE model is depending on the image has produced high energy that received from object. The energy received is determined by illumination radiation source and the features of reflectance of the object itself. Applying this model on the APH gives more details in the IR image and the IR night vision images show like as in the morning. The performance quality metrics for the suggested approach are entropy, average gradient, contrast, and Sobel edge magnitude. Simulation results reveal the success of the proposed approach in enhancing the quality of IR images.
机译:本文提出了一种用于红外(IR)图像的新型增强算法。该建议的算法将自适应平台直方图均衡(APH)和同态过滤增强(CHFE)的倒谱系的益处混合。这种方法的主要思想取决于将APH应用于IR图像上。然后,通过使用CHFE在频域上施加所得到的图像。该CHFE模型取决于图像产生的高能量从物体接收。接收的能量由照明辐射源和物体本身的反射率的特征决定。在APH上应用此模型在IR图像中提供了更多细节,而IR夜视图像显示如早上。建议方法的性能质量指标是熵,平均梯度,对比度和Sobel边缘幅度。仿真结果揭示了提高IR图像质量的提出方法的成功。

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