Combination of hybrid median filter and total variation minimisation for medical X‐ray image restoration

A 4K-Capable FPGA Implementation of Single Image Haze Removal Using Hazy Particle Maps

“…As a result, the filter may leave halo artifacts in the areas of corners or lines with depth discontinuities. To overcome this drawback, a hybrid median filter (HMF) is needed to ensure corner areas with depth discontinuities [36]. Since outdoor scenes display a series of hazy distributions, it is better to use the median filter in areas with depth continuities and the HMF in areas with depth discontinuities.…”

Normal curvature‐induced variational model for image restoration

“…One of the most famous regularisation terms is the total variation (TV) regulariser, which was first proposed for image denoising [6] and turned out to be very effective for removing noise while preserving image edges. Owing to its good ability to preserve edges, TV has been widely applied to many image processing inverse problems [7][8][9][10][11][12][13][14]. Since edges in an image lead to outliers in the regularisation term, then Fu et al [15] propose the l 1 norm-based regularisation for image restoration, which is closely related to the TV regularisation method.…”

Hybrid higher‐order total variation model for multiplicative noise removal

“…In the earlier stage, the classic methods, such as spatial filtering methods [4, 5] and wavelet‐based methods [6–8], play an important role for MNR. More recently, owing to the successful of regularisation theory, the variational regularisation methods, the maximum a posteriori (MAP)‐based methods, and the sparse representation‐based methods have been widely used for many image processing tasks, such as inpainting, compressive sensing, restoration, and reconstruction [9–14]. Thus, the variational regularisation method also becomes a promising research way for MNR.…”