Objective: Phase unwrapping is a key step of InSAR (Interferometric Synthetic Aperture Radar) data processing. Apply the statistical cost network flow algorithm  (SNAPHU) to high resolution airborne InSAR data. Once the interferogram has phase inconsistencies caused by lines of trees, the unwrapped result appears large areas of phase jump along inconsistencies correspondingly. SNAPHU is a global optimization algorithm, which has limitations in dealing with local phase inconsistencies. Local phase inconsistencies can be optimized by local algorithm. Phase inconsistencies can be described by residues. Local data can be optimized by residues compensation. This paper proposes an airborne unwrapping algorithm combines the residue degradation with the statistical-cost network-flow, which has advantages of both the local optimum and the global optimum. Method: Flatten the filtered interferogram. Then apply the residue degradation to the flattened interferogram. The residue degradation process contains residues detection and residues compensation. According to properties of residues and values of neighborhood pixels, these residues will be compensated, and keep iterating to decrease the number of residues to optimize local data. According to calibration parameters of airborne InSAR system, modify parameters and the geometric mode in statistical-cost network-flow (SNAPHU) algorithm. And the modified SNAPHU algorithm is employed for phase unwrapping. Finally, applied a median filter to the unwrapped image to get the final result. Result: The efficiency and accuracy of proposed method is tested and validated by using the single pass dual antenna airborne InSAR data covering Jiangyou, Sichuan areas in 2011. Wooded areas are low coherence and have serious phase inconsistencies, and testing results show that, the proposed algorithm significantly shrunk error unwrapped regions, and fixed large phase jump which are caused by wooded areas. Conclusion: The residue degradation process effectively solves the problem of large unwrapped phase jump, and becomes more robust to noise.