Optimized Pap Smear Image Enhancement: Hybrid PMD Filter-CLAHE Using Spider Monkey Optimization
This work addresses image quality improvement for Pap smear analysis, which is incremental as it combines existing techniques with optimization.
The study tackled enhancing Pap smear image quality for cervical cancer detection by introducing a hybrid PMD filter-CLAHE method optimized with spider monkey optimization, achieving an average EME of 5.45, RMS contrast of 60.45, MC of 0.995, and entropy of 6.80.
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.