文件名称:Regularized_Newton_Residual_algorithm

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一种使用牛顿迭代的超分辨算法,该算法以2的对数提高传统Landweber算法的运算速度,附带文章。-The problem of poor resolution of acquired image in the passive millimeter wave imaging stems mainly from antenna size limitations, thus necessitating efficient post-processing to achieve resolution improvements. A novel image super-resolution algorithm, Regularized-Newton-Residual (RNR) algorithm, is proposed for Passive Millimeter wave imaging (PMMW). First Newton inversion algorithm is introduced into the field of image restoration. The iterative scheme of Newton algorithm is deduced based on normal equation. Then, residual method is employed to achieve better performance and implement spectrum extrapolation. Experimental results demonstrate the algorithm is insensitive to noise distribution. Furthermore it has high super-resolution rate and fast convergence speed.
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正则化Newton增量超分辨算法\estsnr.m

..........................\landweber13.m

..........................\max2.m

..........................\min2.m

..........................\min2newton.m

..........................\min2newton_increment.m

正则化Newton增量超分辨算法

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