基于 ℓ1 范数与梯度约束的无人机图像拼接方法

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关键词：无人机影像;图像拼接;多模态;特征匹配;范数约束;梯度优化;图切割;泊松融合 中图分类号：TP391.41 文献标志码：A doi：10.12415/j.issn.1671-7872.25019

Abstract： Unmanned aerial vehicle （UAV）image stitching technology provides crucial support for the development of the low-altitude economy through eficient integration of aerial data.To addressisues such as low registration accuracy， misalignment，and ghosting caused by insufficient feature point extraction in low-texture UAV images，an （204号 ℓ1 -norm and gradient-constrained UAV image stitching method was proposed.First， feature points and feature lines of the target image and the reference image were jointly extracted to construct a multi-feature descriptor，enhancing matching robustness and effectively improving image misalignment. Second， the ℓ1 -norm wasused for color difference measurement， and an energy function was constructed with gradient constraints to guide the seam to preferentially pass through highly similar continuous regions.Finally，the graph-cut algorithm wasapplied to search for the optimal stitching path in the overlapping area，and Poison blending was employed to achieve a natural transition at the stitching boundary.Two sets of typical drone image datasets were selected，and comparative tests with three mainstream methods （SPW，LPC，and MSF） were conducted to verify the superiority of the proposed method in terms of stitching accuracy and visual efects.The results show that compared with SPW，LPC，and MSF， the SsIM values of the proposed method are improved by 2.97% ， 5.87% ，and 3.07% respectively，while the PSNR values are increased by0.595，0.848，0.841 dB respectively. In terms of visual effects， misalignment and ghosting during the stitching processare significantly improved by the proposed method， with structural integrityand texture details of objects being beter preserved，resulting in enhanced overallquality of UAV image stitching.Both quantitative and qualitative analyses fully demonstrate the superior performance of the proposed method in lowtexture scenarios.

Keywords： UAV imagery; image stitching; multimodal; feature matching; norm constraints; gradient optimization; graph cut;Poisson fusion

随着低空经济上升为国家战略性新兴产业，无人机技术在物流运输、生态保护、基础设施巡检等领域展现出巨大应用潜力。（剩余12156字）