Multi-frame low-resolution image super-resolution reconstruction method based on convex combination mode
A super-resolution reconstruction and low-resolution image technology, which is applied in the field of computer vision, can solve the problems of large deviation of the overall gray value of the pixel and holes, etc., and achieve the effect of denoising, high precision and improvement effect
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[0037] Procedure 1, Implementing the Joint Estimation Method to Generate High-Resolution Image I joint
[0038] (1.1) The method of super-resolution reconstruction first needs to obtain data such as motion estimation parameters and image blur parameters to perform reconstruction. However, the obtained parameters cannot be guaranteed to be completely accurate, and small errors in the parameters will be amplified during the reconstruction process. Therefore, if we can find a way to reduce the cumulative effect of parameter errors, the effect of super-resolution reconstruction will be improved to a certain extent. So the joint method reformulates the super-resolution reconstruction framework as follows:
[0039] X ^ = argmin X ^ { Σ k = 1 N f ( Y k - ...
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