  With the exponential growth in data volume, especially in recent decades, the
demand for data processing has surged across all scientific fields. Within
astronomical datasets, the combination of solar space missions and ground-based
telescopes has yielded high spatial and temporal resolutions for observing the
Sun, thus fueling an increase in the utilization of automatic image processing
approaches. Image processing methodologies play a pivotal role in analyzing
solar data, a critical component in comprehending the Sun's behavior and its
influence on Earth. This paper provides an overview of the utilization of
diverse processing techniques applied to images captured from the solar
photosphere. The introduction of our manuscript furnishes a description of the
solar photosphere along with its primary characteristics. Subsequently, we
endeavor to outline the significance of preprocessing photospheric images, a
crucial prerequisite before engaging in any form of analysis. The subsequent
section delves into an examination of numerous reputable sources that have
employed image processing methodologies in their research pertaining to the
Sun's surface. This section also encompasses discussions concerning recent
advancements in image processing techniques for solar data analysis and their
potential implications for future solar research. The final section deliberates
on post-processing procedures as supplementary steps that are essential for
deriving meaningful results from raw data. Effectively, this paper imparts
vital information, offering concise explanations regarding the Sun's surface,
the application of image processing techniques to various types of photospheric
images, indispensable image preprocessing stages, and post-processing
procedures aimed at transforming raw data into coherent and comprehensive
insights.
