Deep learning for pixel-level image fusion: Recent advances and future prospects
By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …
composite image, pixel-level image fusion is recognized as having high significance in a …
Convolutional dictionary learning: A comparative review and new algorithms
Convolutional sparse representations are a form of sparse representation with a dictionary
that has a structure that is equivalent to convolution with a set of linear filters. While effective …
that has a structure that is equivalent to convolution with a set of linear filters. While effective …
Convolutional sparse coding for image super-resolution
Sparse coding (SC) plays an important role in versatile computer vision applications such as
image super-resolution (SR). Most of the previous SC based SR methods partition the image …
image super-resolution (SR). Most of the previous SC based SR methods partition the image …
ALISTA: Analytic weights are as good as learned weights in LISTA
Deep neural networks based on unfolding an iterative algorithm, for example, LISTA
(learned iterative shrinkage thresholding algorithm), have been an empirical success for …
(learned iterative shrinkage thresholding algorithm), have been an empirical success for …