Accurate and efficient extraction of glacier extents is crucial for understanding the glacier's climatic response characteristics and timely evaluating the processes and impacts of glacier changes under a warming climate. The threshold-based segmentation method, as a simple and efficient extraction technique, has been widely applied in non-debris-covered glacier delineation. However, the presence of seasonal snow and water bodies, which exhibit reflectance characteristics similar to glacier ice in specific wavelength ranges, can lead to classification errors when traditional ice/snow indices are used for glacier boundary delineation. To improve the accuracy of glacier mapping, this study proposed a novel and simple ice/snow index, Whiteness Difference Index (WDI), based only on visible bands, which fully exploits the high reflectance of ice/snow in the visible bands and is specifically designed for mapping non-debris-covered glaciers. Time-series WDI maps, free from cloud and water body pixel contamination, were used to calculate the Snow Cover Frequency Index (SFI), which helps reduce errors caused by seasonal snow as its dynamic variations are characterized by lower frequency values. By applying the mapping algorithm to non-debris-covered glaciers in the Puruogangri Mountain using 2020 Landsat-8 images available on Google Earth Engine (GEE), the results demonstrate that the proposed method significantly reduces misclassifications caused by seasonal snow and water bodies. Compared with the result of manual delineation, this method achieves an area error of less than 1 % and higher accuracy scores (Kappa: 0.94; Overall Accuracy: 96.97 %). We also applied this method on the annual mapping of Puruogangri Ice Cap and successfully detected area changes and surging behavious of several glaciers in the region. And we assessed the transferability of the algorithm by applying it to additional major glaciated mountain regions and across different optical satellite sensors, thus demonstrating this method is suitable for non-debris-covered glacier mapping while maintaining high classification accuracy, providing an methodological support for regional glacier change analysis.