Options
System Design of Perceptual Quality-Regulable H.264 Video Encoder
Date Issued
2011
Date
2011
Author(s)
Fu, Yu-Jie
Abstract
With the development of video coding standard from MPEG-1, MPEG-2, H.263 to H.264/AVC, the coding efficiency improves step by step. The video coding standard, H.264/AVC, offers tens of to hundreds of compression ratio and has improved the coding efficiency a lot better than before. However, the final receiver of the video information is human. The video coding standard only uses SAD (sum of absolute difference) or SSD (sum of square difference) as the quality metrics which are poorly correlated with human perception. Thus the bit allocation of the video bit stream is usually not utilized efficiently for the human perception. With the proper allocation of bits, such as more bits for more important or more distorted region, the total quality can be improved.
In this work, we develop a system of perceptual quality-regulable H.264 video encoder. Exploiting the relationship between the reconstructed macroblock and its best predicted macroblock from mode decision, a novel predictive quantization parameter estimation method is built and used to regulate the video quality according to a predefined perceptual quality. An automatic scheme of quality refinement is also developed to a better usage of bit budget. Moreover, with the aid of salient object detection, we further improve the quality on where human might focus on.
The proposed algorithm achieves better bit allocation for video coding system by changing quantization parameters at macroblock level. Compared to JM reference software with macroblock layer rate control, our algorithm achieves better and more stable quality by the higher average SSIM index and smaller SSIM variation.
For hardware implementation, We propose a salient object detection hardware engine since the salient object detection can be used not only in video coding but also in many other applications such as automatic image cropping, adaptive image display in small devices, object recognition, and tracking. The design is implemented with TSMC90nm technology. The processing capability is HDTV1080p(1920x1080) with 30 frame per second.
In this work, we develop a system of perceptual quality-regulable H.264 video encoder. Exploiting the relationship between the reconstructed macroblock and its best predicted macroblock from mode decision, a novel predictive quantization parameter estimation method is built and used to regulate the video quality according to a predefined perceptual quality. An automatic scheme of quality refinement is also developed to a better usage of bit budget. Moreover, with the aid of salient object detection, we further improve the quality on where human might focus on.
The proposed algorithm achieves better bit allocation for video coding system by changing quantization parameters at macroblock level. Compared to JM reference software with macroblock layer rate control, our algorithm achieves better and more stable quality by the higher average SSIM index and smaller SSIM variation.
For hardware implementation, We propose a salient object detection hardware engine since the salient object detection can be used not only in video coding but also in many other applications such as automatic image cropping, adaptive image display in small devices, object recognition, and tracking. The design is implemented with TSMC90nm technology. The processing capability is HDTV1080p(1920x1080) with 30 frame per second.
Subjects
perceptual coding
h.264 video encoder
quality regulable
Type
thesis
File(s)
No Thumbnail Available
Name
ntu-100-R98943015-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):5fbeef0f05a3b0b74b4ab0d4bd0ff62a