Brief review of image denoising techniques

Visual Computing for Industry, Biomedicine, and Art

Linwei Fan¹  Caiming Zhang¹  Hui Fan²  Fan Zhang² 

[1] School of Software, Shandong University;Shandong Co-Innovation Center of Future Intelligent Computing;

关键词: Image denoising;    Non-local means;    Sparse representation;    Low-rank;    Convolutional neural network;   

DOI  :  10.1186/s42492-019-0016-7

来源: DOAJ

【 摘 要 】

Abstract With the explosion in the number of digital images taken every day, the demand for more accurate and visually pleasing images is increasing. However, the images captured by modern cameras are inevitably degraded by noise, which leads to deteriorated visual image quality. Therefore, work is required to reduce noise without losing image features (edges, corners, and other sharp structures). So far, researchers have already proposed various methods for decreasing noise. Each method has its own advantages and disadvantages. In this paper, we summarize some important research in the field of image denoising. First, we give the formulation of the image denoising problem, and then we present several image denoising techniques. In addition, we discuss the characteristics of these techniques. Finally, we provide several promising directions for future research.

【 授权许可】

Unknown