NDLI: Image smoothing via truncated ℓ0 gradient regularisation

Content Provider	IET Digital Library
Author	He, Liangtian Wang, Yilun
Abstract	Edge-preserving image smoothing aims at maintaining the fundamental constituents, i.e. salient edges of a given image, while removing the noise and insignificant details in the meantime. It is often employed at the pre-processing step of many image processing tasks, including reconstruction, segmentation, recognition and three-dimensional content generation, to name just a few. Recently, a sparse gradient counting scheme in an optimisation framework has attracted much attention, and it confines the discrete number of intensity changes among neighbouring pixels. This ℓ 0 -regularised sparsity pursuit scheme performs favourably in a global optimisation manner. However, it often achieves unsatisfactory performance at diminishing trivial details and at smoothing discrete regions. In this study, a new image smoothing scheme with truncated ℓ 0 regularisation is proposed, which is especially effective for sharpening critical edges. For objective evaluation of the smoothing performance, images are linearly quantised into several layers to generate the experimental images, then these quantised images are smoothed using several methods for reconstructing the smoothly changed shape and intensity of the original images. Compared with the ℓ 0 smoothing scheme, extensive experimental results demonstrate that the proposed method performs much better at preserving main structures and removing trivial details.
Starting Page	226
Ending Page	234
Page Count	9
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 2, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0533
Journal	IET Image Processing
Publisher Date	2017-09-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Edge Detection Edge Preserving Image Smoothing Gradient Method Gradient Regularisation Image Recognition Image Reconstruction Image Segmentation Image Smoothing Noise Removal Optical, Image And Video Signal Processing Optimisation Technique Salient Edge Sparse Gradient Counting Scheme
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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