Journal article Open Access

Image Fusion using Non Subsampled Contourlet Transform in Medical Field

Jampani Ravi,; M. Gowri Sri Durga; Y. D. R. Ch. Kartheek; MD. Shabeena Begum; T. Raju; T. V. Syamala Raju

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:contributor>Blue Eyes Intelligence Engineering  &amp; Sciences Publication(BEIESP)</dc:contributor>
  <dc:creator>Jampani Ravi,</dc:creator>
  <dc:creator>M. Gowri Sri Durga</dc:creator>
  <dc:creator>Y. D. R. Ch. Kartheek</dc:creator>
  <dc:creator>MD. Shabeena Begum</dc:creator>
  <dc:creator>T. Raju</dc:creator>
  <dc:creator>T. V. Syamala  Raju</dc:creator>
  <dc:description>Image fusion is a powerful method and developing field in the area of image processing. The image fusion is a type of methodology that combines the two or more images into single more informative image. Image fusion is the process of assimilation of numerous input images into a new single fused image with highly informative than the input image. There are various image fusion transform techniques are proposed. Out of that techniques a Non-subsampled Counterlet transform includes shift invariant property, highly directionality, reduced the cost and more efficient information as compared to previous techniques such as wavelet transform(WT), DWT, LWT, MWT, CWT, Curvelet transform, Contourlet transform. In NSCT, we decompose the images into low frequency and high frequency using sparse representation and absolute-maximum rule respectively. The DGSR algorithm is used for the better performance of SR-based approach. Finally, to reconstruct the image we use inverse NSCT and output is fused image.</dc:description>
  <dc:source>International Journal of Engineering and Advanced Technology (IJEAT) 9(3) 3829-3832</dc:source>
  <dc:subject>Image fusion, NSCT, SPARSE, SENSOR.</dc:subject>
  <dc:subject>Retrieval Number</dc:subject>
  <dc:title>Image Fusion using Non Subsampled Contourlet  Transform in Medical Field</dc:title>
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