Jang, Hoon-Seok Muhammad, Mannan Saeed Yun, Guhnoo Kim, Dong Hwan 2024-01-19T19:32:17Z 2024-01-19T19:32:17Z 2021-09-02 2019-08 2076-3417 https://pubs.kist.re.kr/handle/201004/119719 Recovering three-dimensional (3D) shape of an object from two-dimensional (2D) information is one of the major domains of computer vision applications. Shape from Focus (SFF) is a passive optical technique that reconstructs 3D shape of an object using 2D images with different focus settings. When a 2D image sequence is obtained with constant step size in SFF, mechanical vibrations, referred as jitter noise, occur in each step. Since the jitter noise changes the focus values of 2D images, it causes erroneous recovery of 3D shape. In this paper, a new filtering method for estimating optimal image positions is proposed. First, jitter noise is modeled as Gaussian or speckle function, secondly, the focus curves acquired by one of the focus measure operators are modeled as a quadratic function for application of the filter. Finally, Kalman filter as the proposed method is designed and applied for removing jitter noise. The proposed method is experimented by using image sequences of synthetic and real objects. The performance is evaluated through various metrics to show the effectiveness of the proposed method in terms of reconstruction accuracy and computational complexity. Root Mean Square Error (RMSE), correlation, Peak Signal-to-Noise Ratio (PSNR), and computational time of the proposed method are improved on average by about 48%, 11%, 15%, and 5691%, respectively, compared with conventional filtering methods. English MDPI IMAGE FOCUS DEPTH MAP RECOVERY STATE Sampling Based on Kalman Filter for Shape from Focus in the Presence of Noise Article 10.3390/app9163276 1 APPLIED SCIENCES-BASEL, v.9, no.16 APPLIED SCIENCES-BASEL 9 16 scie scopus 000484444100070 2-s2.0-85070867022 Chemistry, Multidisciplinary Engineering, Multidisciplinary Materials Science, Multidisciplinary Physics, Applied Chemistry Engineering Materials Science Physics Article IMAGE FOCUS DEPTH MAP RECOVERY STATE shape from focus (SFF) jitter noise focus curve Kalman filter