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Optimal Deep Rate Control for Intra Coding in High-Efficiency Video Coding Standard.

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Titel: Optimal Deep Rate Control for Intra Coding in High-Efficiency Video Coding Standard.
Autoren: Rezaei, Mehdi, Nakhaei, Arshnoos, Rahimi, Yaser, Jafari, Pouria
Quelle: International Journal of Industrial Electronics Control & Optimization; Dec2025, Vol. 8 Issue 4, p356-362, 7p
Schlagwörter: VIDEO coding, CONVOLUTIONAL neural networks, BIT error rate, REAL-time computing
Abstract (English): This paper proposes a novel Optimal Deep Rate Controller (ODRC) designed for intracoding configuration of the High-Efficiency Video Coding standard. The ODRC incorporates a Convolutional Neural Network-based Rate-Quantization Model (CRQM) to effectively predict bits consumption across the entire Quantization Parameter (QP) range at the Coding Tree Unit (CTU) level. The proposed rate controller employs an optimization algorithm to minimize the buffering delay required for video communications. By establishing a specific search space through the CRQM, a greedy search algorithm is utilized to determine the optimal frame-level QP, thereby minimizing discrepancies between buffer occupancy and target occupancy. Unlike CTU-level rate controllers, which can introduce quality variations due to QP fluctuations among CTUs, the frame-level ODRC maintains consistent objective quality across CTUs within a frame. The ODRC is integrated within the standard reference software HM-16.20. Comparative evaluations with the default rate controller, RC-HM, in the same software, demonstrate the superior performance of ODRC in terms of both delay and bit error ratio. Experimental results indicate that ODRC achieves a notably lower average buffering delay of 0.02s and a lower bit error ratio of 11.25%, in contrast to RC-HM's 0.3s and 44.72%, respectively, emphasizing its effectiveness for HEVC low-delay applications. [ABSTRACT FROM AUTHOR]
Abstract (Arabic): المقال يركز على تطوير وحدة تحكم معدل عميق مثالي (ODRC) لتشفير الإطارات داخل معيار ترميز الفيديو عالي الكفاءة (HEVC). تستخدم ODRC نموذج معدل-كمية قائم على الشبكات العصبية التلافيفية (CRQM) للتنبؤ بدقة باستهلاك البتات عبر معلمات الكم المختلفة (QPs) على مستوى وحدة شجرة التشفير (CTU)، بهدف تقليل تأخيرات التخزين المؤقت في اتصالات الفيديو. تظهر النتائج التجريبية أن ODRC تتفوق بشكل كبير على وحدة التحكم في المعدل الافتراضية (RC-HM) من حيث تأخير التخزين المؤقت ونسبة خطأ البت، حيث تحقق تأخير تخزين مؤقت متوسط أقل يبلغ 0.02 ثانية ونسبة خطأ بت تبلغ 11.25%، مقارنةً بـ 0.3 ثانية و44.72% لوحدة التحكم RC-HM على التوالي. هذا التقدم يضع ODRC كحل مناسب للتطبيقات ذات الكمون المنخفض التي تتطلب نقل فيديو فعال. [Extracted from the article]
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Datenbank: Complementary Index
Beschreibung
Abstract:This paper proposes a novel Optimal Deep Rate Controller (ODRC) designed for intracoding configuration of the High-Efficiency Video Coding standard. The ODRC incorporates a Convolutional Neural Network-based Rate-Quantization Model (CRQM) to effectively predict bits consumption across the entire Quantization Parameter (QP) range at the Coding Tree Unit (CTU) level. The proposed rate controller employs an optimization algorithm to minimize the buffering delay required for video communications. By establishing a specific search space through the CRQM, a greedy search algorithm is utilized to determine the optimal frame-level QP, thereby minimizing discrepancies between buffer occupancy and target occupancy. Unlike CTU-level rate controllers, which can introduce quality variations due to QP fluctuations among CTUs, the frame-level ODRC maintains consistent objective quality across CTUs within a frame. The ODRC is integrated within the standard reference software HM-16.20. Comparative evaluations with the default rate controller, RC-HM, in the same software, demonstrate the superior performance of ODRC in terms of both delay and bit error ratio. Experimental results indicate that ODRC achieves a notably lower average buffering delay of 0.02s and a lower bit error ratio of 11.25%, in contrast to RC-HM's 0.3s and 44.72%, respectively, emphasizing its effectiveness for HEVC low-delay applications. [ABSTRACT FROM AUTHOR]
ISSN:26453517