ABSTRACT Distribution of straw incorporation in soil is a key indicator of the effectiveness of straw return. Due to the complexity and time consumption of conventional methods, this study employed three image processing techniques—second‐order moments of grey‐scale histogram (HSM), Optimized Area‐weighted Uniformity Index (OAU)and Principal Component Analysis (PCA)—along with a custom‐designed soil stratified sampling tool. Straw samples were divided into 8 layers from top to bottom (0–15 cm depth), with 40 sampling points analyzed. The evaluation model for straw incorporation uniformity within each layer was established by using single image methods and dual‐image combination methods. Results showed that incorporated straw was predominantly concentrated in the 0–10 cm depth range, with straw content decreasing significantly with depth ( p < 0.05) and exhibiting a strong negative correlation (Pearson correlation coefficient = 0.86) with the coefficient of variation. The PCA method was insensitive to soil color variation. In typical straw distribution, the average relative error for PCA was 5.5%, compared to 11.5% for HSM and 11.25% for OAU. Dual‐image combination methods outperformed single image approaches, with the OAU‐PCA combination yielding the highest accuracy (coefficient of determination = 0.90, mean absolute error = 0.03). These findings provide a reliable, efficient tool for field evaluation of straw distribution uniformity, addressing the critical gap between laboratory research and field application. The proposed methodology offers significant potential for optimizing tillage implement design, improving straw decomposition modeling, and enhancing nutrient cycling in conservation tillage systems, particularly in cold regions with slower decomposition rates.