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Found 5 papers, 2 papers with code
RPCANet: Deep Unfolding RPCA Based Infrared Small Target Detection
Deep learning (DL) networks have achieved remarkable performance in infrared small target detection (ISTD).
VEDA: Uneven light image enhancement via a vision-based exploratory data analysis model
Then, a weighted averaging strategy based on the residual image is designed to obtain the output image by combining enhanced results at multiple scales.
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing
In this work, we propose a DUN called low-rank CS network (LR-CSNet) for natural image CS.
AGPCNet: Attention-Guided Pyramid Context Networks for Infrared Small Target Detection
Infrared small target detection is an important problem in many fields such as earth observation, military reconnaissance, disaster relief, and has received widespread attention recently.
Total Variation with Overlapping Group Sparsity and Lp Quasinorm for Infrared Image Deblurring under Salt-and-Pepper Noise
To improve the sparse characteristics of the image while maintaining the image edges and weakening staircase artifacts, this paper proposes a method that uses the Lp quasinorm instead of the L1 norm and for infrared image deblurring with an overlapping group sparse total variation method.
