AGF-based multi-focus image fusion method and system

Abstract

The invention belongs to the technical field of optical image processing and discloses an AGF-based multi-focus image fusion method and system. The method comprises the steps of firstly smoothing an input image by using joint bilateral filtering, and alternately using a source image and a filtered image as the input image and a guide image of bilateral filtering; performing filtering processing onthe bilaterally filtered image by using median filtering to obtain a basic layer and a detail layer of the source image; calculating gradient energy of neighborhood windows of pixels of the basic layer and the detail layer of the source image, establishing a decision matrix according to the gradient energy of the neighborhood windows of the pixels of the basic layer and the detail layer, and fusing the pixels corresponding to the basic layer and the detail layer according to a certain fusion rule. The accuracy of judging a focus region in the source image can be effectively improved and the quality of a fused image can be greatly improved.

Description

technical field

[0001] The invention belongs to the technical field of optical image processing, and in particular relates to an AGF-based multi-focus image fusion method and system. Background technique

[0002] Due to the limitation of depth of field, the optical sensor imaging system can only clearly image part of the scene within the focus range, and only the scene objects within the focus range are clear. Such partially focused images with clear targets cannot accurately and completely describe the scene, thereby limiting people's accurate analysis and understanding of the scene. Analyzing a considerable number of similar images is a waste of time and effort, and also wastes storage space. This will inevitably limit the efficiency and quality of related tasks such as object detection and recognition. Multi-focus image fusion is one of the effective technical ways to solve the above problems by integrating the salient and clear features of multiple images in the same s...

Examples

Embodiment example 1

[0124] Following the scheme of the present invention, this implementation case 1 is figure 2 The two source images shown in (a) and (b) are fused, and the processing results are as follows image 3 Shown in Propose. Simultaneously use Laplacian (LAP), wavelet transform (DWT), non-subsampling based contourlet transform (NSCT), principal component analysis (PCA) method, spatial frequency (SF), robust principal component analysis (RPCA) , Cartoon Texture Image Decomposition (CTD), Guided Filtering (GFF) eight image fusion methods figure 2 The two source images shown in (a) and (b) are fused, and the quality of the fused images of different fusion methods is evaluated, and the results are shown in Table 1.

[0125] Table 1 Multi-focus image 'Disk' fusion image quality evaluation.

[0126]

Embodiment example 2

[0128] Following the scheme of the present invention, this implementation case is Figure 4 The two source images shown in (a) and (b) are fused, and the processing results are as follows Figure 5 Shown in Proposed.

[0129] Simultaneous Laplacian (LAP), wavelet transform (DWT), non-subsampling based contourlet transform (NSCT), principal component analysis (PCA) method, spatial frequency (SF), robust principal component analysis (RPCA), Eight image fusion methods of cartoon texture image decomposition (CTD) and guided filtering (GFF) Figure 4 The two source images (a) and (b) shown are fused, and the quality of the fused images of different fusion methods is evaluated, and the results shown in Table 2 are calculated.

[0130] Table 2 Multi-focus image 'Toy' fusion image quality evaluation.

[0131]

[0132] In Table 1 and Table 2: Method represents the method; the fusion method includes eight types: Laplacian (LAP), wavelet transform (DWT), non-subsampling-based conto...

technical field

[0001] The invention belongs to the technical field of optical image processing, and in particular relates to an AGF-based multi-focus image fusion method and system. Background technique

[0002] Due to the limitation of depth of field, the optical sensor imaging system can only clearly image part of the scene within the focus range, and only the scene objects within the focus range are clear. Such partially focused images with clear targets cannot accurately and completely describe the scene, thereby limiting people's accurate analysis and understanding of the scene. Analyzing a considerable number of similar images is a waste of time and effort, and also wastes storage space. This will inevitably limit the efficiency and quality of related tasks such as object detection and recognition. Multi-focus image fusion is one of the effective technical ways to solve the above problems by integrating the salient and clear features of multiple images in the same s...

Examples

Embodiment example 1

[0124] Following the scheme of the present invention, this implementation case 1 is figure 2 The two source images shown in (a) and (b) are fused, and the processing results are as follows image 3 Shown in Propose. Simultaneously use Laplacian (LAP), wavelet transform (DWT), non-subsampling based contourlet transform (NSCT), principal component analysis (PCA) method, spatial frequency (SF), robust principal component analysis (RPCA) , Cartoon Texture Image Decomposition (CTD), Guided Filtering (GFF) eight image fusion methods figure 2 The two source images shown in (a) and (b) are fused, and the quality of the fused images of different fusion methods is evaluated, and the results are shown in Table 1.

[0125] Table 1 Multi-focus image 'Disk' fusion image quality evaluation.

[0126]

Embodiment example 2

[0128] Following the scheme of the present invention, this implementation case is Figure 4 The two source images shown in (a) and (b) are fused, and the processing results are as follows Figure 5 Shown in Proposed.

[0129] Simultaneous Laplacian (LAP), wavelet transform (DWT), non-subsampling based contourlet transform (NSCT), principal component analysis (PCA) method, spatial frequency (SF), robust principal component analysis (RPCA), Eight image fusion methods of cartoon texture image decomposition (CTD) and guided filtering (GFF) Figure 4 The two source images (a) and (b) shown are fused, and the quality of the fused images of different fusion methods is evaluated, and the results shown in Table 2 are calculated.

[0130] Table 2 Multi-focus image 'Toy' fusion image quality evaluation.

[0131]

[0132] In Table 1 and Table 2: Method represents the method; the fusion method includes eight types: Laplacian (LAP), wavelet transform (DWT), non-subsampling-based conto...

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