Open AccessDefocused image restoration method based on micro-nano scale
Author(s) -
Yongjun Liu,
Qiuyu Wu,
Mingxin Zhang,
Yi Wang
Publication year - 2021
Publication title -
characterization and application of nanomaterials
Language(s) - English
Resource type - Journals
ISSN - 2578-1995
DOI - 10.24294/can.v4i2.1335
Subject(s) - artificial intelligence , computer vision , preprocessor , focus (optics) , computer science , nanoscopic scale , scale (ratio) , top hat transform , noise (video) , image (mathematics) , grid , optics , image quality , image restoration , materials science , inverse , microscopy , pattern recognition (psychology) , image processing , feature detection (computer vision) , mathematics , physics , nanotechnology , geometry , quantum mechanics
An image adaptive noise reduction enhancement algorithm based on NSCT is proposed to perform image restoration preprocessing on the defocused image obtained under the microscope. Defocused images acquired under micro-nano scale optical microscopy, usually with inconspicuous details, edges and contours, affect the accuracy of subsequent observation tasks. Due to its multi-scale and multi-directionality, the NSCT transform has superior transform functions and can obtain more textures and edges of images. Combined with the characteristics of micro-nanoscale optical defocus images, the NSCT inverse transform is performed on all sub-bands to reconstruct the image. Finally, the experimental results of the standard 500nm scale grid, conductive probe and triangular probe show that the proposed algorithm has a better image enhancement effect and significantly improves the quality of out-of-focus images.