Image fusion technique using DT-CWT

Sruthy, S; Parameswaran, Latha; Sasi, Anumol

doi:10.1109/imac4s.2013.6526400

Cited by 35 publications

(14 citation statements)

References 6 publications

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“…The advantage of this method over averaging method is that there is no compromise made over the good information available in the input images. But the disadvantage is that it considers only the higher pixel intensity as the better information ignoring all other values [4].…”

Section: Select Maximum Methodsmentioning

confidence: 99%

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Comparative Study and Analysis of Medical Image Fusion Techniques

Parekh¹,

Patel²,

Macwan³

et al. 2014

IJCA

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Section: Select Maximum Methodsmentioning

confidence: 99%

“…This method also has the disadvantage of either completely considering information or discarding it fully [4].…”

Section: Select Minimum Methodsmentioning

confidence: 99%

Comparative Study and Analysis of Medical Image Fusion Techniques

Parekh¹,

Patel²,

Macwan³

et al. 2014

IJCA

View full text Add to dashboard Cite

show abstract

“…This is the easiest method of image fusion where intensity of output pixel is the average intensity of all the corresponding pixels from the input images [15]. But, this method yields image with reduced contrast as unwanted side-effects.…”

Section: Fusion Methods Based On Averagingmentioning

confidence: 99%

“…Quality is a characteristic that measures perceived image degradation i.e., in comparison with ideal or perfect image [15]. The evaluation plays a major role in the development of efficient image fusion techniques.…”

Section: Evaluation Of Image Fusionmentioning

confidence: 99%

An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization

Singh¹,

Banga²

2014

IJCA

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Image fusion fuses the information from several images of one scene to obtain a precise, complete and reliable image which is more appropriate for human visual perception or additional vision processing. The quality of an image is closely related to image focus. The discrete cosine transforms (DCT) based methods of image fusion are more suitable and time-saving in real-time systems using DCT based standards of still image or video. DCT based image fusion produced results but with lesser clarity, less PSNR value and more Mean square error. This paper proposes a new algorithm whose overall objective is to improve the results by combining DCT with adaptive histogram equalization. The experimental results and comparison has shown that the proposed algorithm provides a significant improvement over the existing DCT based fusion techniques.

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“…Wavelet transformations offer a more compact way to fuse images and are based on the primary concept of injecting the detail information, usually present in the high-frequency data, from each source image into the final fused image. A significant body of literature exists on wavelet-based approaches [101], and more recent research can be found in the literature [109]- [112]. In 2011, an Army Research Laboratory technical report compared 13 algorithms for multimodal fusion, including spatial approaches, pyramid approaches, and several currently available wavelet-based algorithms.…”

Section: Eq 18mentioning

confidence: 99%

A wavelet-based framework for efficient processing of digital imagery with an application to helmet-mounted vision systems

Hoke¹

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I would like to thank my family for their never-ending support through this process from the time I started (and received) my Masters through the completion of this journey to finish my Doctorate. Your words of encouragement, trips to visit, and the couple occasional times you had to talk me off the "ledge" of potentially throwing in the towel were critical to my success. I could not have achieved this goal without you. I would also like to thank all those at work who supported me in various ways. First, my "work dads", David W. Jensen and Steven Koenck, thank you for so many reasons. You gave me a shot by hiring me for the internship that sparked my passion for image processing and led to many fascinating projects in the first couple years of my career. You never hesitated to be an ear when I needed to discuss work, school, and life in general and continued to provide moral support and motivation even after I moved on to other groups at work. Thank you to the managers I had while I was going through this process for allowing me the flexibility to work and go to school at the same time: Alex Postnikov, Scott Zogg, and Christina Conway. And also a huge thanks to Jason Wenger and Jason Ramapuram for supporting the software implementation.

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Image fusion technique using DT-CWT

Cited by 35 publications

References 6 publications

Comparative Study and Analysis of Medical Image Fusion Techniques

Comparative Study and Analysis of Medical Image Fusion Techniques

An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization

A wavelet-based framework for efficient processing of digital imagery with an application to helmet-mounted vision systems

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