A novel rate control algorithm for video coding based on fuzzy-PID controller

Rate control algorithms (RCAs) aim to achieve the best visual quality under the minimum bit rate and the limited buffer size. A self-parameter-tuning fuzzy-PID controller is proposed to reduce the deviation between the target buffer level and the current buffer fullness. Fuzzy logic is used to tune each parameter of the proportional-integral-derivative controller by selecting appropriate fuzzy rules through simulation in H.264/advanced video coding (AVC). To control the quality fluctuation between consecutive frames, a quality controller is adopted. The proposed RCA has been implemented in an H.264/AVC video codec, and our experimental results show that the proposed algorithm achieves smooth target bits while enabling better buffer control and visual quality

No-reference image and video quality assessment: a classification and review of recent approaches

The field of perceptual quality assessment has gone through a wide range of developments and it is still growing. In particular, the area of no-reference (NR) image and video quality assessment has progressed rapidly during the last decade. In this article, we present a classification and review of latest published research work in the area of NR image and video quality assessment. The NR methods of visual quality assessment considered for review are structured into categories and subcategories based on the types of methodologies used for the underlying processing employed for quality estimation. Overall, the classification has been done into three categories, namely, pixel-based methods, bitstream-based methods, and hybrid methods of the aforementioned two categories. We believe that the review presented in this article will be helpful for practitioners as well as for researchers to keep abreast of the recent developments in the area of NR image and video quality assessment. This article can be used for various purposes such as gaining a structured overview of the field and to carry out performance comparisons for the state-of-the-art methods