Journal ArticleDOI
Multifocus noisy image fusion using contourlet transform
R. Srivastava,Ashish Khare +1 more
TLDR
In this article, the authors proposed a method for noisy image fusion in contourlet domain, where the fusion algorithm is combined with a denoising algorithm to reverse the effect of noise.Abstract:
Image fusion is a challenging area of research with a variety of applications. The process of image fusion collects information from different sources and combines them in a single composite image. The composite fused image can better describe the scene than any of the source images. In this paper, we have proposed a method for noisy image fusion in contourlet domain. The proposed method works equally well for fusion of noise free images. Contourlet transform is a multiscale, multidirectional transform with various aspect ratios. These properties make it more suitable for image fusion than other conventional transforms. In the proposed work, the fusion algorithm is combined with a denoising algorithm to reverse the effect of noise. In the proposed method, we have used a level dependent threshold that is based on standard deviation of contourlet coefficients, mean and median of the absolute contourlet coefficients. Experimental results demonstrate that the proposed method performs well in the prese...read more
Citations
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Journal ArticleDOI
Multi-focus image fusion algorithm based on Laplacian pyramids.
TL;DR: This paper proposes a method named region mosaicking on Laplacian pyramids (RMLP) to fuse multi-focus images that are captured by microscope and shows that RMLP has the best performance in quantitative comparison with other methods.
Journal ArticleDOI
A multi-focus image fusion method via region mosaicking on Laplacian pyramids.
TL;DR: In this paper, a method named Region Mosaicking on Laplacian Pyramids (RMLP) is proposed to fuse multi-focus images that is captured by microscope and has best performance in quantitative comparison with other methods.
Journal ArticleDOI
Intrinsic Image Decomposition-Based Grey and Pseudo-Color Medical Image Fusion
Jiao Du,Weisheng Li,Heliang Tan +2 more
TL;DR: Two algorithms based on intrinsic image decomposition to decompose MRI and PET images into its two separate components in the spatial domain are proposed and demonstrate that the proposed fusion methods could improve the values of mutual information by the metrics on the disease database.
Journal ArticleDOI
Threshold based Image Fusion in Dual Tree Complex Wavelet Domain
Richa Srivastava,Ashish Khare +1 more
TL;DR: The experimental results show that the proposed method outperforms all the other state-of- the-art methods visually as well quantitatively as in terms of standard deviation, mutual information, edge strength, fusion factor, sharpness and average gradient.
References
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Book
Fundamentals of digital image processing
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Journal ArticleDOI
The Laplacian Pyramid as a Compact Image Code
Peter J. Burt,Edward H. Adelson +1 more
TL;DR: A technique for image encoding in which local operators of many scales but identical shape serve as the basis functions, which tends to enhance salient image features and is well suited for many image analysis tasks as well as for image compression.
Journal ArticleDOI
The contourlet transform: an efficient directional multiresolution image representation
Minh N. Do,Martin Vetterli +1 more
TL;DR: A "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information is pursued and it is shown that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves.
Journal ArticleDOI
Multisensor data fusion: A review of the state-of-the-art
TL;DR: A comprehensive review of the data fusion state of the art is proposed, exploring its conceptualizations, benefits, and challenging aspects, as well as existing methodologies.
Journal ArticleDOI
A wavelet-based image fusion tutorial
TL;DR: This tutorial performs a synthesis between the multiscale-decomposition-based image approach, the ARSIS concept, and a multisensor scheme based on wavelet decomposition, i.e. a multiresolution image fusion approach.