Abstract: In-service polyethylene (PE) pipelines may develop defects such as material thinning and cracks on their external surfaces, significantly compromising the structural integrity and safety of the pipelines. This paper focused on exploring key technologies for microwave detection and quantitative visualization assessment of defects on the external surfaces of PE pipelines. Through numerical simulations, the response characteristics of microwave detection signals in the Ka-band to defects of various sizes on the external surfaces were investigated. Simultaneously, a microwave detection experimental system was constructed, and a clutter suppression method based on singular value decomposition was proposed. High-precision defect imaging was achieved through a spectral reconstruction algorithm, followed by image fusion based on the maximum pixel value. Eventually, quantitative evaluation of defects was conducted utilizing image threshold segmentation and the Regionprops statistical function. The research findings demonstrated that the proposed detection and processing methods enabled high-precision quantitative assessment of defect visualization. The localization accuracy of external surface defects was within 1 mm, while the assessment accuracy of planar dimensions can exceed 90%.