This chapter introduces the fundamental concepts of image noise and techniques for smoothing and enhancement. Common noise types such as salt-and-pepper noise and random noise are analysed, followed by a comparison of major spatial filters, including the moving average, median, and Gaussian filters. Their characteristics, strengths, and limitations in noise suppression and edge preservation are discussed in detail. The chapter further examines contrast enhancement methods, including linear stretching and histogram equalisation, and explains their applicability through grayscale distribution analysis. Finally, advanced dehazing using the dark channel prior and morphological operations for binary-image denoising are presented. Together, these methods provide essential foundations for reliable image preprocessing.