泛场景自适应优化的多输出最小二乘SVR光谱反射率重建方法

Multi-output Least-squares SVR Spectral Reflectance Reconstruction Method Based on Adaptive Optimization in Multi-scene

针对传统回归模型在多种场景光谱重建中存在的泛化性能较差的问题,提出一种自适应优化的多输出最小二乘支持向量回归光谱反射率重建方法,满足泛场景下最优光谱重建模型应用需求。首先使用多输出最小二乘支持向量回归作为重建模型,该模型具有良好的收敛速度及小样本拟合精度。同时为了提高模型在多种场景下的泛化性能,提出一种融合拟合精度与变化趋势,且具有自适应权重的综合评价指标,作为混沌麻雀搜索算法的适应度函数,对重建模型进行不同场景的参数动态寻优,解决特定场景的模型参数最优化问题。实验结果表明,在不同彩绘文物参考色块光谱重建中,该方法的平均光谱均方根误差降低了0.0292、适应度系数提高了1.29%、色差降低了3.38,能够针对不同重建场景自适应优化模型参数,在不同重建场景中均获得了较好的光谱反射率重建效果。

Spectral reflectance is considered as the“fingerprint information”of substances,which can reflect the essential properties of the color of substances.The true color of the substance under different light conditions can be accurately restored by obtaining the spectral reflectance information.It has important applications in printing,mural pigment recognition,textile and other scenes.Spectral reflectance reconstruction technology based on multispectral imaging has been widely used in recent years.It has the advantages of non-contact,high efficiency,diversified use scene and so on.The working process can be seen as using the low-dimensional multi-channel response signals output by various imaging devices to reconstruct the high-dimensional spectral reflectivity information of the object.Regression model method is widely used in spectral reconstruction because it has advantages in the model applicability of spectral reconstruction with small samples.The reconstruction accuracy in specific scenes has been continuously improved through the existing regression model reconstruction methods,but the optimization of model parameters in different reconstruction scenes has not been solved.The model is not adaptive enough to achieve the optimal effect of spectral reconstruction in multi-scene.To solve the problem of poor generalization performance of traditional regression model in spectral reconstruction of many scenes,multioutput least-square support vector regression spectral reflectance reconstruction method based on adaptive optimization in multi-scene is proposed to meet the application requirements of optimal spectral reconstruction model in multi-scene.Firstly,multi-output least square support vector regression is used as the reconstruction model,which simplifies the convex quadratic programming problem of traditional multioutput support vector regression.It improves the convergence speed of the model.Secondly,by combining the mean absolute percentage error and Pearson correlation coefficient,a comprehensive evaluation index of the model with adaptive weight is proposed,which can take into account the fitting accuracy and trend of the spectral reflectance reconstruction model.It is used as the fitness function of the sparrow search algorithm to optimize the parameters of the spectral reconstruction model,which can improve the generalization performance of the model.Simultaneously,Chebyshev chaotic map is introduced to initialize the sparrow search algorithm to prevent it from falling into local optimization in the process of optimization.Finally,the spectral reflectance of the test samples is reconstructed by using the reconstruction model with optimal parameters.To verify the effectiveness of this method,213 standard RAL color cards are used as experimental data.Monochromatic CCD cameras and 10 narrowband filters are used as multispectral imaging systems.Compared with other traditional reconstruction methods,the average spectral root mean square error is reduced by 0.0840,the average fitness coefficient is increased by 0.69%,and the average chromatic aberration is reduced by 1.23%.To verify the reconstruction effect of this method in different scenes,five different color regions on the temple murals and ancient painted cultural relics in a temple are selected for spectral reconstruction experiments.Compared with others,the average spectral root mean square error of this method is reduced by 0.0292,the fitness coefficient is increased by 1.29%,and the color difference is reduced by 3.38%.The model parameters can be adaptively optimized for different reconstruction scenes,and better spectral reflectance reconstruction results are obtained in different reconstruction scenes.The experimental results show that this method can meet the requirements of highprecision color restoration of murals and painted cultural relics in practical application.