SINGLE-IMAGE SUPER RESOLUTION AND DENOISING USING MULTIPLE WAVELET DOMAIN SPARSITY

摘要

A computer-implemented method of enhancing images includes receiving one or more observed images, identifying wavelet bases, and determining a downsampling operator. A noise variance value is estimated and used to select a tuning parameter. A blurring kernel is estimated based on one or more system calibration parameter and used to determine a low-pass blurring filter operator. A cost function is created which generates one or more denoised super-resolution images based on the observed images and the plurality of wavelet bases. The cost function may include, for example, a sparsity inducing norm applied to the plurality of wavelet bases (with the tuning parameter applied to the sparsity inducing norm) and a constraint requiring the one or more denoised super-resolution images to be equal to a result of applying the low-pass blurring filter operator and the downsampling operator to the one or more denoised super-resolution images. The one or more denoised super-resolution images are generated by minimizing this cost function.