This paper reviews the research status and application progress of sub-pixel edge detection algorithms. First， three traditional edge detection algorithms （gradient-based， statistical-based， and structured edge detection algorithms） are briefly introduced， and their limitations in edge detection accuracy are analyzed. Then， the concept of sub-pixel edge detection and its advantages in improving edge detection precision are elaborated. Subsequently， three major sub-pixel edge detection methods （interpolation method， fitting method， and moment method） are discussed in detail regarding their theoretical foundations， algorithmic principles， and application characteristics. Comparative analysis shows that these methods can achieve high-precision edge detection in different application scenarios. Finally， the paper summarizes the main existing challenges in sub-pixel edge detection technology and provides future research prospects from aspects of noise suppression， modal optimization， and technology integration.