View in EDS HTML Full Text PDF Full Text

Modified Holoentropy based arithmetic coding for ROI based image compression and data transmission.

Saved in:
Bibliographic Details
Title: Modified Holoentropy based arithmetic coding for ROI based image compression and data transmission.
Authors: Sankaran, Sarath V.1 (AUTHOR) ss3067@srmist.edu.in, Jayaseeli, J. D. Dorathi1 (AUTHOR)
Source: Imaging Science Journal. Oct2025, Vol. 73 Issue 7, p859-877. 19p.
Subjects: Image compression, Lossless data compression, Data transmission systems, Lossy data compression, Data compression, Entropy (Information theory), Image processing
Abstract: This Paper proposes a modified Holoentropy Based Arithmetic coding (AC) for ROI image compression. Here, the ROI extraction is done under two compressions they are lossless and lossy compression. First, the lossless compression on the ROI region is applied using Lembel-Ziv-Welch (LZW). Meanwhile, the lossy compression on the Non-ROI region is applied by using forward transform and Quantization. Then, the modified Holoentropy-based AC is applied to obtain a compressed bit stream in both scenarios. The two compressed bit streams are fused with the label to generate the compressed data. In the decompression phase, inverse LZW, Inverse modified AC, Inverse Quantization and Inverse transform are applied to generate a non-ROI image. The generated RoI image and non-RoI image are fused to obtain the original image. The proposed method has a minimum Mean Squared Error of 0.055, a Peak Signal-to-Noise Ratio (PSNR) of 43.451 dB, and a Structural Similarity Index (SSIM) of 0.975. [ABSTRACT FROM AUTHOR]
Copyright of Imaging Science Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 188316755
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Modified Holoentropy based arithmetic coding for ROI based image compression and data transmission.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Sankaran%2C+Sarath+V%2E%22">Sankaran, Sarath V.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ss3067@srmist.edu.in</i><br /><searchLink fieldCode="AR" term="%22Jayaseeli%2C+J%2E+D%2E+Dorathi%22">Jayaseeli, J. D. Dorathi</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Imaging+Science+Journal%22">Imaging Science Journal</searchLink>. Oct2025, Vol. 73 Issue 7, p859-877. 19p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Image+compression%22">Image compression</searchLink><br /><searchLink fieldCode="DE" term="%22Lossless+data+compression%22">Lossless data compression</searchLink><br /><searchLink fieldCode="DE" term="%22Data+transmission+systems%22">Data transmission systems</searchLink><br /><searchLink fieldCode="DE" term="%22Lossy+data+compression%22">Lossy data compression</searchLink><br /><searchLink fieldCode="DE" term="%22Data+compression%22">Data compression</searchLink><br /><searchLink fieldCode="DE" term="%22Entropy+%28Information+theory%29%22">Entropy (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This Paper proposes a modified Holoentropy Based Arithmetic coding (AC) for ROI image compression. Here, the ROI extraction is done under two compressions they are lossless and lossy compression. First, the lossless compression on the ROI region is applied using Lembel-Ziv-Welch (LZW). Meanwhile, the lossy compression on the Non-ROI region is applied by using forward transform and Quantization. Then, the modified Holoentropy-based AC is applied to obtain a compressed bit stream in both scenarios. The two compressed bit streams are fused with the label to generate the compressed data. In the decompression phase, inverse LZW, Inverse modified AC, Inverse Quantization and Inverse transform are applied to generate a non-ROI image. The generated RoI image and non-RoI image are fused to obtain the original image. The proposed method has a minimum Mean Squared Error of 0.055, a Peak Signal-to-Noise Ratio (PSNR) of 43.451 dB, and a Structural Similarity Index (SSIM) of 0.975. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Imaging Science Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=188316755
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/13682199.2025.2499390
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 859
    Subjects:
      – SubjectFull: Image compression
        Type: general
      – SubjectFull: Lossless data compression
        Type: general
      – SubjectFull: Data transmission systems
        Type: general
      – SubjectFull: Lossy data compression
        Type: general
      – SubjectFull: Data compression
        Type: general
      – SubjectFull: Entropy (Information theory)
        Type: general
      – SubjectFull: Image processing
        Type: general
    Titles:
      – TitleFull: Modified Holoentropy based arithmetic coding for ROI based image compression and data transmission.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Sankaran, Sarath V.
      – PersonEntity:
          Name:
            NameFull: Jayaseeli, J. D. Dorathi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: Oct2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 13682199
          Numbering:
            – Type: volume
              Value: 73
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Imaging Science Journal
              Type: main
ResultId 1