@InProceedings{8553482,
  author = {P. Astola and I. Tabus},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Light Field Compression of HDCA Images Combining Linear Prediction and JPEG 2000},
  year = {2018},
  pages = {1860-1864},
  abstract = {We have proposed under JPEG Pleno standardization activities a scheme for lenslet image compression, where the regularities and similarities existing between neighbor angular views were successfully exploited, achieving competitive results in the JPEG Pleno core experiments using lenslet data. This paper proposes improvements on our previous scheme of light field compression, making our approach more suitable for compression of light fields acquired with dense camera arrays, where the disparities between farthest views can reach several hundreds of pixels. We review the functional blocks of the compression algorithm, replacing and modifying some of the functionality with more advanced and efficient solutions. Based on our submission to the JPEG Pleno core experiments, we present and discuss our results obtained on the Fraunhofer HDCA dataset. Additionally, we present a new view merging algorithm which substantially increases the PSNR at all bit rates.},
  keywords = {cameras;data compression;image coding;image denoising;image reconstruction;image resolution;light;light field compression;HDCA images;linear prediction;JPEG 2000;lenslet image compression;JPEG Pleno core experiments;light fields;compression algorithm;PSNR;Encoding;Transform coding;Image coding;Cameras;Quantization (signal)},
  doi = {10.23919/EUSIPCO.2018.8553482},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437976.pdf},
}

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This paper proposes improvements on our previous scheme of light field compression, making our approach more suitable for compression of light fields acquired with dense camera arrays, where the disparities between farthest views can reach several hundreds of pixels. We review the functional blocks of the compression algorithm, replacing and modifying some of the functionality with more advanced and efficient solutions. Based on our submission to the JPEG Pleno core experiments, we present and discuss our results obtained on the Fraunhofer HDCA dataset. 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Tabus},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Light Field Compression of HDCA Images Combining Linear Prediction and JPEG 2000},\n year = {2018},\n pages = {1860-1864},\n abstract = {We have proposed under JPEG Pleno standardization activities a scheme for lenslet image compression, where the regularities and similarities existing between neighbor angular views were successfully exploited, achieving competitive results in the JPEG Pleno core experiments using lenslet data. This paper proposes improvements on our previous scheme of light field compression, making our approach more suitable for compression of light fields acquired with dense camera arrays, where the disparities between farthest views can reach several hundreds of pixels. We review the functional blocks of the compression algorithm, replacing and modifying some of the functionality with more advanced and efficient solutions. Based on our submission to the JPEG Pleno core experiments, we present and discuss our results obtained on the Fraunhofer HDCA dataset. 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