کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4970379 | 1450123 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new compressive sensing video coding framework based on Gaussian mixture model
ترجمه فارسی عنوان
یک چارچوب برنامه نویسی حسگر فشرده سازی جدید مبتنی بر مدل مخلوط گاوس
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In this paper, we specifically design an efficient compressive sensing video (CSV) coding framework for the CSV system, by considering the distribution characteristics of the CSV frame. To explore the spatial redundancy of the CSV, the CSV frame is first divided into blocks and each block is modeled by a Gaussian mixture model (GMM), and then it is compressed by a product vector quantization. We further explore the temporal redundancy of the CSV by encoding the adjacent CSV frames by the differential pulse code modulation technique and the arithmetic encoding technique. Experiment results show that the proposed CSV coding solution maintains low coding complexity, which is required by the CSV system. Meanwhile, it achieves significant BD-PSNR improvement by about 7.13-11.41Â dB (or equivalently 51.23-66.96% bitrate savings) compared with four existing video coding solutions, which also have low computational complexity and suit for the CSV system.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 55, July 2017, Pages 66-79
Journal: Signal Processing: Image Communication - Volume 55, July 2017, Pages 66-79
نویسندگان
Xiangwei Li, Xuguang Lan, Meng Yang, Jianru Xue, Nanning Zheng,