Open AccessAdaptive Directional Cubic Convolution for Integrated Circuit Chip Defect Image Interpolation
Author(s) -
Y. Chào,
Chengxia Ma,
Wentao Shan,
Jie Feng,
Zhisheng Zhang
Publication year - 2021
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2021.15.117
Subject(s) - bicubic interpolation , interpolation (computer graphics) , artificial intelligence , computer vision , convolution (computer science) , pixel , computer science , bilinear interpolation , thresholding , enhanced data rates for gsm evolution , stairstep interpolation , demosaicing , algorithm , image processing , image (mathematics) , multivariate interpolation , color image , artificial neural network
An adaptive directional cubic convolution interpolation method for integrated circuit (IC) chip defect images is proposed in this paper, to meet the challenge of preserving edge and texture information. In the proposed method, Otsu thresholding technique is employed to distinguish strong edge pixels from weak ones and texture regions, and estimate the direction of strong edges, adaptively. Boundary pixels are pre-interpolated using the original bicubic interpolation method to help improve the interpolation accuracy of the interior pixels. The experimental results of both classic test images and IC chip defect images demonstrate that the proposed method outperforms the competing methods with better edge and texture preservation, interpolation quality, more natural visual effect of the interpolated images and reasonable computational time. The proposed method can provide high quality IC chip images for defect detection and has been successfully applied on practical vision inspection for IC chips