盲目反卷积光谱图超分辨复原算法

反卷积是实现光谱图超分辨复原的重要手段，与常规反卷积相比，盲目反卷积具有不需要预先准确获取卷积核函数的优势。着眼于充分利用光谱信号的特点和已有的光谱图反卷积成果，详细讨论了空域迭代盲目反卷积方法用于光谱图反卷积时的算法实现问题，并在分析光谱图卷积退化过程的基础上，针对光谱图反卷积算法特点，提出了光谱图卷积退化简化计算模型和最小二乘高斯拟合模型，以解决算法中相应的计算问题。基于Matlab平台的仿真表明，对于所用的高斯型谱线和点扩散函数，空域迭代盲目反卷积算法效果良好，在信噪比为50 dB时，分辨率提高约30％。

Blind Deconvolution Algorithm for Spectrogram Super-Resolution Restoration

Deconvolution is an important way to realize spectrogram super-resolution restoration. Blind deconvolution is superior to the traditional one in that it does not need a well prepared convolution core. Taking advantages of the features of spectrogram and the existing achievements of spectrogram deconvolution, the authors bring forward a scheme to adapt the space domain itera- tive blind deconvolution method to spectroscopy application. Moreover, after probing into the spectrogram degradation described by convolution, computational models for spectrum convolution and Gauss fitting are worked out to meet the requirements of blind deconvolution algorithm. Accompanying results are simulations with MATLABT. 0. They shows that for the given spectrum and point spread function of Gauss type the blind deconvolution algorithm works well and a resolution enhancement of 30% can be achieved under a signal-to-noise ratio of 50 dB.