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Book ChapterDOI

Real time human visual system based framework for image fusion

TL;DR: A simple yet efficient real time image fusion algorithm is proposed considering human visual properties in spatial domain that is computationally simple and implemented very easily in real-time applications.
Abstract: Image Fusion is a technique which attempts to combine complimentary information from multiple images of the same scene so that the fused image is more suitable for computer processing tasks and human visual system. In this paper, a simple yet efficient real time image fusion algorithm is proposed considering human visual properties in spatial domain. The algorithm is computationally simple and implemented very easily in real-time applications. Experimental results highlights the expediency and suitability of the algorithm and efficiency is carried by the comparison made between proposed and existing algorithm.

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Citations
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Journal ArticleDOI
TL;DR: A novel fusion framework is proposed for multimodal medical images based on non-subsampled contourlet transform (NSCT) to enable more accurate analysis of multimodality images.
Abstract: Multimodal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. In this paper, a novel fusion framework is proposed for multimodal medical images based on non-subsampled contourlet transform (NSCT). The source medical images are first transformed by NSCT followed by combining low- and high-frequency components. Two different fusion rules based on phase congruency and directive contrast are proposed and used to fuse low- and high-frequency coefficients. Finally, the fused image is constructed by the inverse NSCT with all composite coefficients. Experimental results and comparative study show that the proposed fusion framework provides an effective way to enable more accurate analysis of multimodality images. Further, the applicability of the proposed framework is carried out by the three clinical examples of persons affected with Alzheimer, subacute stroke and recurrent tumor.

381 citations


Cites background from "Real time human visual system based..."

  • ...Multimodal medical image fusion not only helps in diagnosing diseases, but it also reduces the storage cost by reducing storage to a single fused image instead of multiple-source images....

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Journal ArticleDOI
TL;DR: A novel framework for medical image fusion based on frame let transform is proposed considering the characteristics of human visual system (HVS) to decompose all source images by the framelet transform.
Abstract: Multi-modal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. In this paper, a novel framework for medical image fusion based on framelet transform is proposed considering the characteristics of human visual system (HVS). The core idea behind the proposed framework is to decompose all source images by the framelet transform. Two different HVS inspired fusion rules are proposed for combining the low- and high-frequency coefficients respectively. The former is based on the visibility measure, and the latter is based on the texture information. Finally, the fused image is constructed by the inverse framelet transform with all composite coefficients. Experimental results highlight the expediency and suitability of the proposed framework. The efficiency of the proposed method is demonstrated by the different experiments on different multi-modal medical images. Further, the enhanced performance of the proposed framework is understood from the comparison with existing algorithms.

105 citations

Journal ArticleDOI
TL;DR: Visual inspection and quantitative evaluation of the fused images obtained by the proposed method, using different evaluation metrics, demonstrate its effectiveness over several existing image fusion methods.

46 citations


Cites methods from "Real time human visual system based..."

  • ...A Human Visual System (HVS) based fusion technique in spatial domain using Noise Visibility Function (NVF) [30] has been shown to be computationally faster and more effective compared to the DWT based method....

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  • ...For all of these images, results of proposed fusion framework are compared with the traditional contrast pyramid [15], traditional DWT based method [18], gradient pyramid [17], PCA based method [11], SIDWT based method [19], and NVF based method [30], and Salience Preserving Fusion [33] (SPF) using the aforementioned metric system....

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  • ...The proposed method’s performance is quite promising and improved compared to the multiscale and multiresolution based methods as well as NVF based method which uses spatial domain image fusion....

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  • ...The code for each fusion method is executed 8 Image name (size) Proposed method Contrast pyramid DWT Gradient pyramid PCA SIDWT NVF SPF Character (256 × 256) 0.0606 0.0538 0.0757 0.1273 0.0328 0.1400 0.0076 2.5875 CircleTriangle (290 × 290) 0.1011 0.0731 0.0860 0.1473 0.0330 0.1666 0.0093 3.0606 Mandrill (500 × 480) 0.2069 0.1617 0.1877 0.3530 0.0376 0.5587 0.0250 9.4601 Ball (128 × 128) 0.0169 0.0397 0.0424 0.0601 0.0307 0.0756 0.0020 0.6372 Battery (256 × 256) 0.0606 0.0660 0.0740 0.1223 0.0321 0.1439 0.0077 2.5513 Lena (512 × 512) 0.2130 0.1748 0.2147 0.4088 0.0438 0.6141 0.0279 10.7456 Balloon (640 × 480) 0.3740 0.2105 0.2670 0.4972 0.0462 0.7168 0.0316 11.6304 Toy (600 × 465) 0.2691 0.1909 0.2374 0.4422 0.0438 0.6496 0.0289 9.7332 Folk (512 × 512) 0.2143 0.1781 0.2126 0.4117 0.0426 0.6099 0.0274 10.9493 Beer (256 × 256) 0.0605 0.0702 0.0659 0.1275 0.0323 0.1479 0.0078 2.5811 Book (1280 × 960) 1.0585 0.7486 1.0979 2.0204 0.0874 3.0250 0.1328 44.1137 Leaves (270 × 205) 0.0623 0.0556 0.0654 0.1006 0.0327 0.1067 0.0055 2.0812 times and the average time for each image set is presented in the table....

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Journal ArticleDOI
TL;DR: A novel image fusion algorithm based on framelet transform based on texture while exploiting the human visual system characteristics can preserve more details in source images and further improve the quality of fused image.
Abstract: In this paper, a novel image fusion algorithm based on framelet transform is presented. The core idea is to decompose all the images to be fused into low and high-frequency bands using framelet transform. For fusion, two different selection strategies are developed and used for low and high-frequency bands. The first strategy is adaptive weighted average based on local energy and is applied to fuse the low-frequency bands. In order to fuse high-frequency bands, a new strategy is developed based on texture while exploiting the human visual system characteristics, which can preserve more details in source images and further improve the quality of fused image. Experimental results demonstrate the efficiency and better performance than existing image fusion methods both in visual inspection and objective evaluation criteria.

29 citations

Proceedings ArticleDOI
10 Nov 2014
TL;DR: This paper represents image fusion technique that will provide better result using Discrete Wave Packet decomposition (DWPT) and optimize result using genetic algorithm (GA) than compare it with Intensity Hue Saturation (IHS) used for image fusion.
Abstract: Image fusion is area of digital image processing which deals with combining the two complimentary images obtained from different sensors into one single image containing the most relevant information of the provided scene. Research domain of image fusion process is very vast. Application of image fusion ranges from medical field to satellite technology. This fused Image obtained after fusion process has characteristics of each input image. Here in our purposed work we want to fuse CT and MRI images. There are various standard method used for image fusion produce that produce good result spatial result but cause spatial noise. In this paper we represent image fusion technique that will provide better result using Discrete Wave Packet decomposition (DWPT) and optimize result using genetic algorithm (GA) than compare it with Intensity Hue Saturation (IHS) used for image fusion. Performance of purposed fusion technique is measured by mean, standard deviation, entropy, variance, mutual information, peak signal to noise ratio (PSNR) and structure similarity.

13 citations


Cites background from "Real time human visual system based..."

  • ...[11] Gaurav Bhatnagar, “Real Time Human Visual System Based Framework for Image Fusion,” Lecture Notes in Computer Science, 2010....

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  • ...Definition of these measures and their physical meanings are given as follows [11]....

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References
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Journal ArticleDOI
01 Jan 1997
TL;DR: This paper provides a tutorial on data fusion, introducing data fusion applications, process models, and identification of applicable techniques.
Abstract: Multisensor data fusion is an emerging technology applied to Department of Defense (DoD) areas such as automated target recognition, battlefield surveillance, and guidance and control of autonomous vehicles, and to non-DoD applications such as monitoring of complex machinery, medical diagnosis, and smart buildings. Techniques for multisensor data fusion are drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation and other areas. This paper provides a tutorial on data fusion, introducing data fusion applications, process models, and identification of applicable techniques. Comments are made on the state-of-the-art in data fusion.

2,356 citations

Journal ArticleDOI
TL;DR: In this article, an image fusion scheme based on the wavelet transform is presented, where wavelet transforms of the input images are appropriately combined, and the new image is obtained by taking the inverse wavelet transformation of the fused wavelet coefficients.

1,532 citations

Proceedings ArticleDOI
11 May 1993
TL;DR: The authors present an extension to the pyramid approach to image fusion that provides greater shift invariance and immunity to video noise, and provides at least a partial solution to the problem of combining components that have roughly equal salience but opposite contrasts.
Abstract: The authors present an extension to the pyramid approach to image fusion. The modifications address problems that were encountered with past implementations of pyramid-based fusion. In particular, the modifications provide greater shift invariance and immunity to video noise, and provide at least a partial solution to the problem of combining components that have roughly equal salience but opposite contrasts. The fusion algorithm was found to perform well for a range of tasks without requiring adjustment of the algorithm parameters. Results were remarkably insensitive to changes in these parameters, suggesting that the procedure is both robust and generic. A composite imaging technique is outlined that may provide a powerful tool for image capture. By fusing a set of images obtained under restricted, narrowband, imaging conditions, it is often possible to construct an image that has enhanced information content when compared to a single image obtained directly with a broadband sensor. >

917 citations


"Real time human visual system based..." refers methods in this paper

  • ...(u) (v) (w) (x) Fused Images using Li method [4] Proposed method...

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  • ...Classical approaches of image fusion are based on additive technique[2], Principal Component Analysis(PCA)[3] and high pass filter merger[4]....

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Journal Article

644 citations


"Real time human visual system based..." refers methods in this paper

  • ...Classical approaches of image fusion are based on additive technique[2], Principal Component Analysis(PCA)[3] and high pass filter merger[4]....

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Book ChapterDOI
29 Sep 1999
TL;DR: A new stochastic approach which can be applied with different watermark techniques based on the computation of a Noise Visibility Function (NVF) that characterizes the local image properties, identifying textured and edge regions where the mark should be more strongly embedded.
Abstract: This paper presents a new stochastic approach which can be applied with different watermark techniques. The approach is based on the computation of a Noise Visibility Function (NVF) that characterizes the local image properties, identifying textured and edge regions where the mark should be more strongly embedded. We present precise formulas for the NVF which enable a fast computation during the watermark encoding and decoding process. In order to determine the optimal NVF, we first consider the watermark as noise. Using a classical MAP image denoising approach, we show how to estimate the ”noise”. This leads to a general formulation for a texture masking function, that allows us to determine the optimal watermark locations and strength for the watermark embedding stage. We examine two such NVFs, based on either a non-stationary Gaussian model of the image, or a stationary Generalized Gaussian model. We show that the problem of the watermark estimation is equivalent to image denoising and derive content adaptive criteria. Results show that watermark visibility is noticeably decreased, while at the same time enhancing the energy of the watermark.

371 citations