The color demosaicing and image scaling based on improve Hamilton-Adams

The demosaicing process is the most critical step in image processing, this study presents a Hamilton-Adams-based algorithm for mosaic removal and image scaling. The algorithm consists of three steps: image pre-processing, image scaling, and improved Hamilton-Adams mosaic removal. The image pre-proc...

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Published inProceedings ... Asia-Pacific Signal and Information Processing Association Annual Summit and Conference APSIPA ASC ... (Online) pp. 892 - 897
Main Authors Peng, Yu-Wen, Hu, Chia-Yu, Chin, Yen-Ju, Chou, He-Sheng, Lin, Yuan-Jin, Liu, Yu-Lin, Chen, Shih-Lun, Chen, Tsung-Yi, Li, Kuo-Chen, Chen, Chiung-An
Format Conference Proceeding
LanguageEnglish
Published IEEE 31.10.2023
Subjects
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ISSN2640-0103
DOI10.1109/APSIPAASC58517.2023.10317437

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Abstract The demosaicing process is the most critical step in image processing, this study presents a Hamilton-Adams-based algorithm for mosaic removal and image scaling. The algorithm consists of three steps: image pre-processing, image scaling, and improved Hamilton-Adams mosaic removal. The image pre-processing stage employs a mean filter to reduce high-frequency signals at the image edges, effectively mitigating the zipper effect caused by image scaling and improving image quality. The improved Hamilton-Adams method incorporates high-quality linear interpolation to achieve more accurate edge computations. In terms of image quality assessment, this paper increased 1.13 dB of PSNR, 1.19 dB of CPSNR, and 0.03 of SSIM values compared to high-quality linear interpolation with bicubic interpolation.
AbstractList The demosaicing process is the most critical step in image processing, this study presents a Hamilton-Adams-based algorithm for mosaic removal and image scaling. The algorithm consists of three steps: image pre-processing, image scaling, and improved Hamilton-Adams mosaic removal. The image pre-processing stage employs a mean filter to reduce high-frequency signals at the image edges, effectively mitigating the zipper effect caused by image scaling and improving image quality. The improved Hamilton-Adams method incorporates high-quality linear interpolation to achieve more accurate edge computations. In terms of image quality assessment, this paper increased 1.13 dB of PSNR, 1.19 dB of CPSNR, and 0.03 of SSIM values compared to high-quality linear interpolation with bicubic interpolation.
Author Lin, Yuan-Jin
Hu, Chia-Yu
Chen, Tsung-Yi
Peng, Yu-Wen
Liu, Yu-Lin
Chen, Shih-Lun
Li, Kuo-Chen
Chin, Yen-Ju
Chou, He-Sheng
Chen, Chiung-An
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  givenname: Chiung-An
  surname: Chen
  fullname: Chen, Chiung-An
  email: joannechen@mail.mcut.edu.tw
  organization: Ming Chi University of Technology,Department of Electrical Engineering,New Taipei City,Taiwan,243303
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Snippet The demosaicing process is the most critical step in image processing, this study presents a Hamilton-Adams-based algorithm for mosaic removal and image...
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StartPage 892
SubjectTerms Color filter array
Demosaicing
Hamilton-Adams
Image color analysis
Image edge detection
Image pre-processing
Image quality
Image scaling
Interpolation
Measurement
Noise reduction
Pipelines
Title The color demosaicing and image scaling based on improve Hamilton-Adams
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