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<records>

  <record>
    <language>eng</language>
          <publisher>Oriental Scientific Publishing Company</publisher>
        <journalTitle>Biosciences Biotechnology Research Asia</journalTitle>
          <issn>0973-1245</issn>
            <publicationDate>2018-09-25</publicationDate>
    
        <volume>15</volume>
        <issue>3</issue>

 
    <startPage>501</startPage>
    <endPage>507</endPage>

	 
      <doi>10.13005/bbra/2655</doi>
        <publisherRecordId>30884</publisherRecordId>
    <documentType>article</documentType>
    <title language="eng">A Survey on the Image Denoising to enhance Medical Images</title>

    <authors>
	 


      <author>
       <name>Bhawna Goyal</name>

 
		
	<affiliationId>1</affiliationId>
      </author>
    

	 


      <author>
       <name>Ayush Dogra</name>


		
	<affiliationId>1</affiliationId>

      </author>
    

	 


      <author>
       <name>Sunil Agrawal</name>

		
	<affiliationId>1</affiliationId>
      </author>
    

	 


      <author>
       <name>B. S. Sohi</name>

		
	<affiliationId>2</affiliationId>
      </author>
    


	


	
    </authors>
    
	    <affiliationsList>
	    
		
		<affiliationName affiliationId="1">UIET, Panjab University Chandigarh.</affiliationName>
    

		
		<affiliationName affiliationId="2">Chandigarh University Gharuan.</affiliationName>
    
		
		
		
		
	  </affiliationsList>






    <abstract language="eng">While acquisition and transmission of images, all recording devices have physical limitations and traits which make them prone to noise. Noise manifests itself in the form of signal perturbation leading to deterred image observation, image analysis and image assessment. Image denoising is fundamental to the world of image processing. Thus any progress made in image denoising forms a stepping stone in our understanding of image processing and statistics. The basic fundamental for denoising of an image includes suppression of the noisy pixels while preserving as many information pixel as possible.. The manuscript provides the reader’s a typical foundation for image denoising.</abstract>

    <fullTextUrl format="html">https://www.biotech-asia.org/vol15no3/a-survey-on-the-image-denoising-to-enhance-medical-images/</fullTextUrl>



      <keywords language="eng">
        <keyword>Gaussian; Image Denoising; Noise; Poisson; Spatial; Transform</keyword>
      </keywords>

  </record>
</records>