Abstract
Pap smear image quality is crucial for cervical cancer detection. This study introduces an optimized hybrid approach that combines the Perona-Malik Diffusion (PMD) filter with contrast-limited adaptive histogram equalization (CLAHE) to enhance Pap smear image quality. The PMD filter reduces the image noise, whereas CLAHE improves the image contrast. The hybrid method was optimized using spider monkey optimization (SMO PMD-CLAHE). BRISQUE and CEIQ are the new objective functions for the PMD filter and CLAHE optimization, respectively. The simulations were conducted using the SIPaKMeD dataset. The results indicate that SMO outperforms state-of-the-art methods in optimizing the PMD filter and CLAHE. The proposed method achieved an average effective measure of enhancement (EME) of 5.45, root mean square (RMS) contrast of 60.45, Michelson's contrast (MC) of 0.995, and entropy of 6.80. This approach offers a new perspective for improving Pap smear image quality.
Abstract (translated)
宫颈癌检测中，巴氏涂片图像的质量至关重要。本研究提出了一种优化的混合方法，结合了佩罗纳-马尔基（Perona-Malik Diffusion, PMD）滤波器和对比度受限自适应直方图均衡化（Contrast-Limited Adaptive Histogram Equalization, CLAHE），以提高巴氏涂片图像的质量。PMD滤波器减少图像噪声，而CLAHE则增强图像对比度。该混合方法使用蜘蛛猴优化算法（SMO PMD-CLAHE）进行了优化。BRISQUE和CEIQ分别是用于PMD滤波器和CLAHE优化的新目标函数。实验数据集采用的是SIPaKMeD数据集。 结果显示，SMO在优化PMD滤波器和CLAHE方面优于现有的先进技术。所提出的方法实现了平均有效增强量（Effective Measure of Enhancement, EME）为5.45，均方根对比度（Root Mean Square Contrast, RMS）为60.45，米氏对比度（Michelson's Contrast, MC）为0.995，熵值为6.80。这种方法为提高巴氏涂片图像质量提供了一种新的视角。
URL
https://arxiv.org/abs/2502.15156
