In this paper a frame-loss adaptive temporal pooling method for video quality assessment is proposed. Extensive
subjective tests have been carried out to determine the duration of successive frames based on which steady quality
judgment can be made by human observers. The resulting duration is applied to the determination of the length of Group
of Frames (GOF), where a flexible algorithm is used to separate the input video into variable sized GOFs. Short-term
temporal pooling is first performed for each of the GOF to get the GOF quality, where quality contribution of each frame
is incorporated with the context and frame loss well taken into account. The video quality is then obtained by long-term
temporal pooling of the GOF quality considering the fact that perceptual video quality is predominately determined by
the worst parts of the video. Extensive experimental results have demonstrated the effectiveness of the proposed method
both for regular and irregular frame loss.
Adaptive Group of Pictures (GOP) is helpful for increasing the efficiency of video encoding by taking account of
characteristics of video content. This paper proposes a method for adaptive GOP structure selection for video encoding
based on motion coherence, which extracts key frames according to motion acceleration, and assigns coding type for
each key and non-key frame correspondingly. Motion deviation is then used instead of motion magnitude in the selection
of the number of B frames. Experimental results show that the proposed method for adaptive GOP structure selection
achieves performance gain of 0.2-1dB over the fixed GOP, and has the advantage of better transmission resilience.
Moreover, this method can be used in real-time video coding due to its low complexity.
Rate control is a central part of standard video codecs. Many rate control schemes including some for JVT video coding
(MPEG-4 AVC /H.264) employ a quadratic formulation of the rate-distortion (R-D) function. The rate control for JVT
video coding is rather complex. In this paper, we analyse the problems existing in the quadratic R-D model and in the
recent rate control scheme for JVT video coding. According to the analysis and experimental results, we present an
improved quadratic R-D model and a frame-layer rate control scheme for JVT video coding based on the model. This
quadratic R-D model is utilized for QP determination in rate control scheme, where the model parameters are estimated
using statistical linear regression analysis. The model is also used for computing the starting quantization step (QP) for
the first frame in the sequence. The Experimental results show that due to the accuracy of the improved quadratic R-D
model, the rate control is quite effective, where the generated bit rates are very close to the target bit rates while
achieving good R-D performance. And the starting QP is very close to the average QP, by which the performance is also
We present an improved method that is suitable for gradient-threshold edge detectors. The method takes into account the basic characteristics of the human visual system and masks the gradient image with the luminance and the activity of local image before edge labeling. An implementation of this method on a Canny detector is described as an example. The results show that the edge images obtained by our algorithm are more consistent with the perceptive edge images.