A new wavelet-based multi-focus image fusion technique using method noise and anisotropic diffusion for real-time surveillance application

2021 ◽  
Author(s):  
Prabhishek Singh ◽  
Manoj Diwakar ◽  
Xiaochun Cheng ◽  
Achyut Shankar
Keyword(s):  
Image Fusion ◽  
Real Time ◽  
Anisotropic Diffusion ◽  
Fusion Technique ◽  
Method Noise ◽  
Focus Image ◽  
Image Fusion Technique ◽  
Surveillance Application

Wavelet-based Multi-focus Image Fusion using Average Method Noise Diffusion (AMND)

2020 ◽  
Vol 13 ◽  
Author(s):  
Prabhishek Singh ◽  
Manoj Diwakar
Keyword(s):  
Image Fusion ◽  
Average Method ◽  
Anisotropic Diffusion ◽  
Visual Sensor ◽  
Edge Preservation ◽  
Fusion Technique ◽  
Visual Appearance ◽  
Method Noise ◽  
Focus Image ◽  
Image Fusion Technique

Aim: This paper presents a new and upgraded wavelet-based multi-focus image fusion technique using average method noise diffusion (AMND). Objective: Improved visual appearance of the final image, no blurring in the final fused image and clearly visible objects (fine edges). Methods: This method extends the standard wavelet-based image fusion technique on multi-focus images by incorporating the hybrid of method noise and anisotropic diffusion in it. This hybrid structure of method noise and anisotropic diffusion is implemented as the post-processing operation in the proposed method. Results: The proposed work shows excellent results in terms of visual appearance and edge preservation. The experimental results of the proposed method are compared with some of the traditional and non-traditional approaches where the proposed method shows comparatively better results. Conclusion: This paper depicts the robustness, effectiveness and adaptive nature of method noise in the field of image enhancement especially in the field of image fusion. The performance of the proposed method is analyzed qualitatively (good visual appearance) and quantitatively (entropy, spatial frequency, and standard deviation). This method has the capability to be incorporated in real-time applications like surveillance in the visual sensor network (VSN).

Efficient Multi Focus Image Fusion Technique Optimized Using MOPSO for Surveillance Applications

2018 ◽  
Vol 14 (3) ◽  
pp. 18-37 ◽  
Author(s):  
Nirmala Paramanandham ◽  
Kishore Rajendiran
Keyword(s):  
Spatial Frequency ◽  
Image Fusion ◽  
Objective Assessment ◽  
Similarity Index ◽  
Absolute Error ◽  
Activity Level ◽  
Fusion Technique ◽  
Focus Image ◽  
Image Fusion Technique ◽  
Surveillance Applications

This article describes how image fusion has taken giant leaps and emerged as a promising field with diverse applications. A fused image provides more information than any of the source images and it is very helpful in surveillance applications. In this article, an efficient multi focus image fusion technique is proposed in cascaded wavelet transform domain using swarm intelligence and spatial frequency (SF). Spatial frequency is used for computing the activity level and consistency verification (CV) based decision map is employed for acquiring the final fused coefficients. Justification for employing SF and CV is also discussed. This technique performs well compared to existing techniques even when the source images are severely blurred. The proposed framework is evaluated using quantitative metrics, such as root mean square error, peak signal to noise ratio, mean absolute error, percentage fit error, structural similarity index, standard deviation, mean gradient, Petrovic metric, SF, feature mutual information and entropy. Experimental outcomes demonstrate that the proposed technique outperforms the state-of-the art techniques, in terms of visual impact as well as objective assessment.

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