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@article{189448,
        author = {Kavya B R and Akhila T},
        title = {Unleashing the Power of Image Preprocessing: A Comprehensive Review of Techniques and Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {6996-7007},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189448},
        abstract = {Image preprocessing is crucial for enhancing image quality and ensuring their relevance in advanced analysis across multiple domains, including medical diagnostics, remote sensing, biometric recognition, and autonomous vehicles. This paper explores essential preprocessing methods like noise removal, contrast enhancement, edge detection, and segmentation, all of which contribute to refining image clarity and overall quality. It also highlights the significance of these techniques in ensuring better performance of downstream tasks, particularly in deep learning models. The paper highlights the challenges associated with preprocessing, such as balancing the removal of noise while preserving important image details and managing the computational overhead. Furthermore, it examines emerging trends, including AI-driven preprocessing methods, real-time image processing for video applications, and the development of Integrated approaches that merge multiple methods for more effective outcomes. The paper concludes by identifying the open challenges and potential avenues for future research that may result in more adaptive, efficient, and accurate preprocessing techniques across diverse domains.},
        keywords = {Gaussian filter, noise reduction, contrast improvement, Histogram equalization, feature extraction, CLAHE, image segmentation, edge detection, grayscale conversion, image denoising, AHE, bilateral filter, Canny edge detection, Prewitt filter, convolutional neural networks, deep learning.},
        month = {December},
        }