Sputum smear microscopy is a primary tool used for the diagnosis of pulmonary TB diseases. Due to its accessibility, minimal bio-safety standards, and cost-effectiveness, the latter is the most preferred test in low- and middle-income countries [26]. De-noising is a fundamental challenge in microscopy image processing because the images are highly corrupted by salt and pepper noise while transmitting. This paper makes a survey on five methods that can be efficiently applied in de-noising the sputum smear microscopy image processing tasks. The five de-noising methods to publish the survey are namely LCD, GPPCM, IMF, ASWMF, and SAF-RGM. The effectiveness of this survey comes along with the metrics such as Peak Signal noise, Root Mean square Error, and the Mean Structure Similarity Index. Many methods for rebuilding spotless images from noisy versions have been proposed. Both the methodology and the outcomes of these methods are dissimilar. This assessment work presents a broad study on image de-noising and suggests a number of promising future research directions.