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Kannan, K.
- Multifocus Image Fusion Using Cloud Model
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Affiliations
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 5, No 2 (2014), Pagination: 944-947Abstract
This paper proposes a multifocus image fusion algorithm based on cloud model. First, each source images are divided into overlapping image blocks of size (2N+1) × (2N+1) and then the mean and entropy of every image pixels over this neighborhood window was calculated and compared in Cloud domain. The pixel with higher magnitude of the calculated image features was selected to form the fused image. The results of multifocus image fusion using this algorithm hold favorable consistency in terms of ischolar_main mean square error, peak signal to noise ratio and quality index for three pairs of test images and confirm the effectiveness of the proposed algorithm.Keywords
Multi Focus Image Fusion, Cloud Model.
- A Statistical Sharpness Measure Based Multi Focus Image Fusion Using Double Density Discrete Wavelet Transform
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Authors
Affiliations
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
2 Department of Computer Science, S.T. Hindu College, IN
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
2 Department of Computer Science, S.T. Hindu College, IN
Source
ICTACT Journal on Image and Video Processing, Vol 3, No 3 (2013), Pagination: 577-582Abstract
Image fusion is the process of combining two or more images of the same scene to form the fused image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. Transform fusion uses transform for representing the source image at multi scale. Due to the compactness, orthogonality and directional information, the Discrete Wavelet Transforms and its undecimated version are used for image fusion. These transforms can be implemented using perfect reconstruction Finite Impulse Response filter banks which are either symmetric or orthogonal. To design filters to have both symmetric and orthogonal properties, the number of filters is increased to generate M-band transform. Double density Discrete Wavelet Transform is an example of M-band DWT and consists of one scaling and two wavelet filters. In this paper, an approach for DDWT based image fusion is designed using statistical property of wavelet filters in representing the sharpness and its performance is measured in terms of Root Mean Square Error, Peak to Signal Noise Ratio, Quality Index.Keywords
Image Fusion, Discrete Wavelet Transform (DWT), Finite Impulse Response Filter, M-Band Transform and Double Density Discrete Wavelet Transform (DDWT).- Removal of Impulsive Noise Using Weighted Fuzzy Mean Filter Based on Cloud Model
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Authors
Affiliations
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, Anna University, Regional Centre, Madurai, IN
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
2 Department of Computer Science and Engineering, Anna University, Regional Centre, Madurai, IN
Source
ICTACT Journal on Image and Video Processing, Vol 4, No 1 (2013), Pagination: 661-666Abstract
This paper proposes a weighted fuzzy mean filter based on cloud model and reports its performance in removing the impulsive noise from the digital image. In addition, the performance of the proposed weighted fuzzy mean filter is compared with already existing variants of median and switching filters using ischolar_main mean square error, peak signal to noise ratio and quality index. Even though the image is corrupted by 90%, this weighted fuzzy mean filter is capable of recovering the original image with good detail preservation.Keywords
Weighted Fuzzy Mean Filter, Cloud Model, Median Filters, Switching Filters.- Optimal Level of Decomposition of Stationary Wavelet Transform for Region Level Fusion of Multi-Focused Images
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Authors
Affiliations
1 Kamaraj College of Engineering and Technology, Tamil Nadu, IN
2 S.T. Hindu College, Tamil Nadu, IN
1 Kamaraj College of Engineering and Technology, Tamil Nadu, IN
2 S.T. Hindu College, Tamil Nadu, IN
Source
ICTACT Journal on Image and Video Processing, Vol 1, No 2 (2010), Pagination: 76-79Abstract
In machine vision, due to the limited depth-of-focus of optical lenses in CCD devices, it is not possible to have a single image that contains all the information of objects in the image. To achieve this, image fusion is required which is usually refers to the process of combining two or more different images, each containing different features into a new single image retaining important features from each and every image with extended information content. The approaches to image fusion can be classified into two namely Spatial Fusion and Transform fusion. The most commonly used transform for image fusion at multi scale is Discrete Wavelet Transform since it minimizes structural distortions. But, wavelet transform suffers from lack of shift invariance and this disadvantage is overcome by Stationary Wavelet Transform. This paper describes the optimum level of decomposition of Stationary Wavelet Transform for region based fusion of multi focused images in terms of various performance measures.Keywords
Image Fusion, Region Level Fusion, Discrete Wavelet Transform and Stationary Wavelet Transform.- Analysis on the Performance of Bilateral Filters in Multi Focused Image Fusion
Abstract Views :136 |
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Authors
Affiliations
1 Department of Mechatronics Engineering, Kamaraj College of Engineering and Technology, IN
1 Department of Mechatronics Engineering, Kamaraj College of Engineering and Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 10, No 4 (2020), Pagination: 2182-2185Abstract
Multi focused image fusion combines two or more images focusing different objects in the same scene to produce all-in-one focus image without artifacts and noises. Among two scale edge preserving filters used in multi focused image fusion, Bilateral Filters plays a vital role since it preserves edge information and avoids staircase effect. This paper analyses the performance of Standard Bilateral Filter (SBF) and its variant Robust Bilateral Filter (RBF) and Weighted Bilateral Filters (WBF) in fusing multi focused images in terms of Quality Index and Mutual Information.Keywords
Image Fusion, Multi focused Images, Bilateral Filters, Quality Index and Mutual Information.References
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