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A new focus measure operator for enhancing image focus in 3D shape recovery
Author(s) -
Jang HoonSeok,
Yun Guhnoo,
Mutahira Husna,
Muhammad Mannan Saeed
Publication year - 2021
Publication title -
microscopy research and technique
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 118
eISSN - 1097-0029
pISSN - 1059-910X
DOI - 10.1002/jemt.23781
Subject(s) - focus (optics) , laplace operator , measure (data warehouse) , window (computing) , pixel , image (mathematics) , computer science , operator (biology) , mathematics , algorithm , image quality , artificial intelligence , mathematical optimization , pattern recognition (psychology) , computer vision , data mining , optics , mathematical analysis , physics , biochemistry , chemistry , repressor , transcription factor , gene , operating system
Abstract Measuring the image focus is an important issue in Shape from Focus methods. Conventionally, the Sum of Modified Laplacian, Gray Level Variance (GLV), and Tenengrad techniques have been used frequently among various focus measure operators for estimating the focus levels in a sequence of images. However, they have various issues such as fixed window size and suboptimal focus quality. To solve these problems, a new focus measure operator based on the adaptive sum of weighted modified Laplacian is proposed. First, the adaptive window size selection algorithm based on the GLV is applied. Next, appropriate weights are assigned to the Modified Laplacian values in the image window based on the distance between the center pixel and neighboring pixels. Finally, the Weighted Modified Laplacian values in the image window are summed. Experimental results demonstrate the effectiveness of the proposed method.