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Novel Image and Its Compressed Image Based on VVC Standard, Pair Data Set for Deep Learning Image and Video Compression Applications

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Computer Vision and Image Processing (CVIP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1777))

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Abstract

More than 80 percent of online traffic is video and image traffic and this will likely rise in the upcoming years. Images and video have multiple dimensions to grow data rate via increasing frame resolution, frame depth, multi-view representation etc. Thus it is very crucial to compress these images and videos efficiently. Lack of sufficient experimental data is a major setback for the development of image and video compression based on deep learning models.

This study presents a new kind of data set for the research community with the goal of advancing the state-of-the-art in image compression using deep learning models. The proposed data set consists of the image and its corresponding VVC (Versatile Video Coding) standard based compressed image as a label of the input image for two quantization parameters. Images from different states of Indian subcontinent area has been captured, containing common objects in their natural context, the beautiful campus of Indian Institute of Technology Madras, which is blessed with rich flora and fauna, and is home to several rare wildlife species, scenes from Himalayas, Clouds in Cherrapunji, Indoor scenes etc. has been captured. The data set will be made publicly to the research community. Statistical analysis of the data set is presented along with VVC compression standard coding analysis.

Indian Institute of Technology Madras.

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Authors and Affiliations

  1. Indian Institute of Technology Madras, Chennai, India

    Rohan lal & Prashant Sharma

  2. Samrat Ashok Technological Institute Vidisha, Vidisha, India

    Devendra Kumar Patel

Authors
  1. Rohan lal
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  2. Prashant Sharma
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  3. Devendra Kumar Patel
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Corresponding author

Correspondence to Rohan lal .

Editor information

Editors and Affiliations

  1. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Deep Gupta

  2. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Kishor Bhurchandi

  3. Indian Institute of Technology Ropar, Rupnagar, India

    Subrahmanyam Murala

  4. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  5. Indian Institute of Technology Roorkee, Roorkee, India

    Sanjeev Kumar

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lal, R., Sharma, P., Patel, D.K. (2023). Novel Image and Its Compressed Image Based on VVC Standard, Pair Data Set for Deep Learning Image and Video Compression Applications. In: Gupta, D., Bhurchandi, K., Murala, S., Raman, B., Kumar, S. (eds) Computer Vision and Image Processing. CVIP 2022. Communications in Computer and Information Science, vol 1777. Springer, Cham. https://doi.org/10.1007/978-3-031-31417-9_33

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  • DOI: https://doi.org/10.1007/978-3-031-31417-9_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31416-2

  • Online ISBN: 978-3-031-31417-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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