Dendroclimatic reconstructions play a key role in contextualizing recent climate change by improving our understanding of past climate variability. The climatically-sensitive blue intensity (BI) parameter is gaining prominence as a more accessible alternative to X-ray densitometry. Yet accurately representing low-frequency trends and high-frequency extremes using scanner-based BI remains a challenge due to color biases and resolution limitations. As part of the REPLICATE project, methodological advances in surfacing and imaging have yielded measurements analogous to BI from ultra-high resolution (~74 700 true dpi) images. Such series from microscope-based sample surface reflected light images, termed surface intensity (SI), represent the binary segmentation of wood anatomy and so approximate anatomical density. The most substantial drawbacks of scanner BI (i.e. discoloration and resolution biases) are bypassed in part by eliminating color altogether and hence low-frequency climatic trends and high-frequency extremes can be better represented. A comparison with multiparameter datasets by Björklund et al. (2019) showed that SI can outperform BI in terms of common (r-bar) and climate signals, and is on par with the best X-ray MXD data. Yet measurement software improvements are still required to unlock the full potential of SI. Ongoing development of these techniques will aid the attainment of unbiased long chronologies by overcoming color biases and resolution issues, but also holds promise for producing surface anatomical (sQWA) datasets from reflected light images. These advances will lead to more accurate tree-ring-based paleoclimatic reconstructions but could also serve a wider range of dendrochronological applications.