@InProceedings{8553456,
  author = {T. Feng and C. Abhayaratne},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Visual Saliency Guided High Dynamic Range Image Compression},
  year = {2018},
  pages = {166-170},
  abstract = {Recent years have seen the emergence of the visual saliency-based image and video compression for low dynamic range (LDR) visual content. The high dynamic range (HDR) imaging is yet to follow such an approach for compression as the state-of-the-art visual saliency detection models are mainly concerned with LDR content. Although a few HDR saliency detection models have been proposed in the recent years, they lack the comprehensive validation. Current HDR image compression schemes do not differentiate salient and non-salient regions, which has been proved redundant in terms of the Human Visual System. In this paper, we propose a novel visual saliency guided layered compression scheme for HDR images. The proposed saliency detection model is robust and highly correlates with the ground truth saliency maps obtained from eye tracker. The results show a reduction of bit-rates up to 50% while retaining the same high visual quality in terms of HDR-Visual Difference Predictor (HDR-VDP) and the visual saliency-induced index for perceptual image quality assessment (VSI) metrics in the salient regions.},
  keywords = {computer vision;data compression;image coding;object detection;Visual saliency guided high dynamic range image compression;visual saliency-based image;low dynamic range visual content;high dynamic range imaging;LDR content;HDR saliency detection models;current HDR image compression schemes;Human Visual System;HDR images;saliency detection model;ground truth saliency maps;high visual quality;HDR-VDP;visual saliency-induced index;perceptual image quality assessment metrics;visual saliency;Visual Difference Predictor;visual saliency detection models;Image coding;Visualization;Saliency detection;Dynamic range;Image segmentation;Europe},
  doi = {10.23919/EUSIPCO.2018.8553456},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570439167.pdf},
}

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Although a few HDR saliency detection models have been proposed in the recent years, they lack the comprehensive validation. Current HDR image compression schemes do not differentiate salient and non-salient regions, which has been proved redundant in terms of the Human Visual System. In this paper, we propose a novel visual saliency guided layered compression scheme for HDR images. The proposed saliency detection model is robust and highly correlates with the ground truth saliency maps obtained from eye tracker. 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Feng and C. Abhayaratne},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Visual Saliency Guided High Dynamic Range Image Compression},\n year = {2018},\n pages = {166-170},\n abstract = {Recent years have seen the emergence of the visual saliency-based image and video compression for low dynamic range (LDR) visual content. The high dynamic range (HDR) imaging is yet to follow such an approach for compression as the state-of-the-art visual saliency detection models are mainly concerned with LDR content. Although a few HDR saliency detection models have been proposed in the recent years, they lack the comprehensive validation. Current HDR image compression schemes do not differentiate salient and non-salient regions, which has been proved redundant in terms of the Human Visual System. In this paper, we propose a novel visual saliency guided layered compression scheme for HDR images. 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