Comparative Analysis of HSV and UV-Based Approaches Denoising Degraded Document Images

Abstract

The restoration of degraded document images is a critical aspect of document image processing. In this study, we present a rigorous comparative analysis of two denoising techniques applied to degraded document images within the HSV and UV color spaces. The primary objective is to quantitatively assess the efficacy of these methods in enhancing the quality of degraded document images. Experiments were conducted using an extensive dataset of degraded document images, and a comprehensive evaluation was performed employing established metrics, including peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean square error (MSE). Results unequivocally demonstrate the superiority of the UV-based approach over the HSV-based method across all evaluation criteria. Specifically, the UV-based approach consistently outperforms the HSV-based approach in PSNR, SSIM, and MSE assessments. Qualitative analysis further underscores the remarkable effectiveness of both techniques in elevating the quality of degraded document images. This study addresses a pressing problem in document image processing by delivering invaluable insights into the comparative efficacy of these denoising techniques. It offers a useful tool for academics and professionals who want to improve the clarity and legibility of deteriorated document images.