Yafeng Zhang, Zexun Geng, Junmin Wang. Multi-focus Image Fusion Algorithm Based on Extended Phase Stretch Transform[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221007
- Laser & Optoelectronics Progress
- Vol. 57, Issue 22, 221007 (2020)
Fig. 1. Results comparison. (a) Operation results by PST; (b) Operation results by Eq. (13)
Fig. 2. Error curve of the calculation result in Fig.1
Fig. 3. Grayscale variance and angle map variance maps of the source images. (a)(d) Blurred and clear source images;(b)(e) grayscale variance of Fig. (a) and (d); (c)(f) angle map variance of Fig. (a) and (d)
Fig. 4. Original image and high-frequency information extraction results. (a)(b) Original images; (c)(d) high-frequency information extracted by kernel function in Ref. [9] and proposed kernel function
Fig. 5. Flow chart of proposed multi-focus image fusion algorithm
Fig. 6. Fusion results of Lytro-07. (a) Fusion result by DWT; (b) fusion result by Laplace operator; (c) fusion result by SR; (d) fusion result by guided filter; (e) fusion result by JCAN; (f) fusion result using the kernel function in Ref. [9]; (g) fusion result using the proposed kernel function
Fig. 7. Difference maps of fusion results. (a)-(g) Corresponding to the difference maps in Fig. 6 (a)--(g)
Fig. 8. Local enlarged drawing. (a)(b) Corresponding to the local enlarged drawing in Fig. 7 (f) and (g)
Fig. 9. Source images and fusion results of proposed algorithm. (a)(b) Source images; (c) fusion results
|
Table 1. Grayscale variance and angle map variance of the blurred and clear images
|
Table 2. Objective evaluation indexes of fusion results
Set citation alerts for the article
Please enter your email address
© Copyright 2018-2021 | Chinese Laser Press. All Rights Reserved 沪ICP备15018463号-20