The DOI matches its Crossref record; 52 of the 55 references it cites were found in a registry or an index.
Visual saliency guided perceptual adaptive quantization based on HEVC intra-coding for planetary images
Open accessAbstract
Due to the limited storage space of spacecraft and downlink bandwidth in the data delivery during planetary exploration, an efficient way for image compression onboard is essential to reduce the volume of acquired data. Applicable for planetary images, this study proposes a perceptual adaptive quantization technique based on Convolutional Neural Network (CNN) and High Efficiency Video Coding (HEVC). This technique is used for bitrate reduction while maintaining the subjective visual quality. The proposed algorithm adaptively determines the Coding Tree Unit (CTU) level Quantization Parameter (QP) values in HEVC intra-coding using the high-level features extracted by CNN. A modified model based on the residual network is exploited to extract the saliency map for a given image automatically. Furthermore, based on the saliency map, a CTU level QP adjustment technique combining global saliency contrast and local saliency perception is exploited to realize a flexible and adaptive bit allocation. Several quantitative performance metrics that efficiently correlate with human perception are used for evaluating image quality. The experimental results reveal that the proposed algorithm achieves better visual quality along with a maximum of 7.17% reduction in the bitrate as compared to the standard HEVC coding.
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“Objects on the surface of Mars exhibit unstructured characteristics with rich textures, ambiguous boundaries and diverse sizes, such as rocks and gravel [21].”
From SegMarsViT: Lightweight Mars Terrain Segmentation Network for Autonomous Driving in Planetary Exploration (2022) · cites this paper as [21]
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Citations
Cites
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“Furthermore, considering that typical onboard remote sensing systems have limited storage and compute capacity, we compare the proposed model with another 4 state-of-the-art lightweight CNN architectures including ShuffleNet_v2 [48], MobileNet_v3 [49], EfficientNet_b0 [50] and GhostNet [51].”
Method
Research works printed but not linked: 3
- N. Moayeri, 1998, A low-complexity, fixed-rate compression scheme for color images and documents, The Hewlett-Packard Journal, 50, 46
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Cited by
Sorted by citations
Dai, Y., Zheng, T., Xue, C., & Zhou, L. (2022) · Remote Sensing · doi:10.3390/rs14246297 · Cited by 35
Self-citationDSFNet: Video Salient Object Detection Using a Novel Lightweight Deformable Separable Fusion Network
Singh, H., Verma, M., & Cheruku, R. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3470045 · Cited by 13
DMFNet: geometric multi-scale pixel-level contrastive learning for video salient object detection
Singh, H., Verma, M., & Cheruku, R. (2025) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-025-00361-z · Cited by 8
Energy-Efficient Saliency-Guided Video Coding Framework for Real-Time Applications
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Quality Enhancement with Frame-wise DLCNN using High Efficiency Video Coding in 5G Networks
Dommeti, V. S., Dharani, M., Shasidhar, K., Reddy, Y. D. R., & Moorthy, T. V. (2024) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v25i2.2658 · Cited by 1
Metadata
- Authors
- Dai, Y., Xue, C., & Zhou, L.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Dai, Yuqi
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2022-02-09
- Volume
- 17
- Issue
- 2
- Pages
- e0263729
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC8827453
- OpenAlex
- W4210855954
- Cited by
- 6
- References
- 55
- Citations by year
- 2025: 2 · 2024: 2 · 2022: 2
- FWCI
- 0.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
- Physical Sciences › Computer Science › Signal Processing › Video Coding and Compression Technologies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Keywords
- visual saliency, planetary images, onboard image compression, quantization parameter adjustment, coding tree unit, saliency maps, ResNet, adaptive bit allocation, bit rate reduction, subjective image quality, spacecraft data storage
- MeSH terms
- Algorithms, Humans, Video Recording, Visual Perception, Planets, Neural Networks, Computer, Spacecraft, Data Compression, Limit of Detection, Satellite Imagery
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