Contrast Enhancement and Noise Reduction Through Synthesizing Gaussian Filter, CLAHE and HE Algorithm for Image Preprocessing

This paper examines a combined approach to contrast enhancement and noise reduction by integrating Gaussian filtering, Contrast- Limited Adaptive Histogram Equalization (CLAHE), and Histogram equalization. (HE) is employed for global contrast enhancement, improving visibility across the entire image by redistributing intensity values. CLAHE is utilized to enhance local contrast while limiting noise amplification by adaptively equalizing intensity in smaller regions. The Gaussian filter complements these techniques by reducing high-frequency noise and smoothing the image, addressing artifacts introduced during contrast enhancement. By combining these algorithms, the proposed method achieves a balanced improvement in image quality, enhancing both global and local contrast while effectively suppressing noise. This synthesis proves especially useful for applications in medical imaging, low-light photography, and remote sensing, where clarity and noise control are critical. Experimental results demonstrate that the sequence of applying these algorithms significantly impacts the output, offering flexibility to prioritize either contrast enhancement or noise suppression depending on the requirements.