A novel approach for multi-focus image fusion based on SF-PAPCNN and ISML in NSST domain
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A novel approach for multi-focus image fusion based on SF-PAPCNN and ISML in NSST domain Liangliang Li 1
& Yujuan Si
1,2
3
4
& Linli Wang & Zhenhong Jia & Hongbing Ma
5
Received: 21 August 2019 / Revised: 29 May 2020 / Accepted: 4 June 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
In order to further improve the contrast and sharpness of fused image, a novel multi-focus image fusion algorithm based on spatial frequency-motivated parameter-adaptive pulse coupled neural network (SF-PAPCNN) and improved sum-modified-laplacian (ISML) in nonsubsampled shearlet transform (NSST) domain is proposed in this paper. In its procedural steps, at first, the source images are decomposed into low-frequency and high-frequency components by NSST. The low-frequency components are fused by SFPAPCNN model, the PAPCNN is designed to estimate the PCNN parameters adaptively according to the input information, and the high-frequency components are fused by ISML model. Finally, the inverse NSST is employed to the fused coefficients to reconstruct the fused image. The superiority of the proposed fusion technique is confirmed by many analytical experimentations on the gray and color multi-focus image data sets. Compared with the state-of-the-art image fusion methods, the proposed fusion algorithm has superior performance in terms of visual inspection and objective evaluation. Keywords Multi-focus image fusion . Spatial frequency (SF) . Parameter-adaptive pulse coupled neural network(PAPCNN) . Sum-modified-laplacian(SML) . Nonsubsampledshearlet transform (NSST)
* Yujuan Si [email protected]
1
College of Communication Engineering, Jilin University, Changchun 130012, China
2
School of Electronic Information Engineering, Zhuhai College of Jilin University, Zhuhai 519041, China
3
School of Mathematics and Information Science, Xinxiang University, Xinxiang 453003, China
4
College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
5
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Multimedia Tools and Applications
1 Introduction Image fusion is an effective method to extract complementary information from multiple sensors, thus, a comprehensive image with more abundant information can be obtained [1]. Multi-focus image fusion is an important branch in the field of image fusion. Due to the limited depth of field of optical sensors, it is difficult to obtain an image with all the scenery focused at the same time. Multi-focus image fusion can fuse multiple images with different focus, and get a clear focus image for all scenes. At present, multi-focus image fusion has broad application prospects in the fields of digital photography, computer vision, target tracking monitoring and microscopic imaging [30, 42]. In recent years, multi-resolution analysis and transformation can better extract the details of the source image and other information, multi-focus image fusion methods based on multiresolution analysis transformation have been
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