A frame-layer bit allocation for H.263+

Abstract

In order to transmit pre-encoded digital video over heterogeneous networks, it is necessary to employ transcoding techniques that convert pre-encoded video streams into different bit rate and quality. The specified problem is referred to as rate shaping or rate adaptation. In this work, we propose a new frame layer bit allocation for H.263+ based video transcoding. In this scheme, scene context statistics from the incoming video stream are utilized to detect scene changes and determine output frame t ypes. Bit budget is allocated to frames according to their energy and frame types. Implementation and experimental results show that the proposed algorithm can improve the video quality and effectively alleviate visual quality degradation after scene changes. This rate adaptation scheme can be used to provide flexible video bit rate adaptation for transmission compressed digital video over heterogeneous networks.

Frame-level bit allocation based on incremental PID algorithm and frame complexity estimation

“…Based on the above observation, some approaches [17,18] allocate bits among video frames by a multi-pass encoding strategy but they are more appropriate for offline encoding. To achieve a real-time optimal framelevel bit allocation, Ribas-Corbera and Li [19] investigated the optimum frame-level bit allocation for H.263 based on the frame complexity. The allocated bits TðjÞ for the jth frame can be defined as…”

Frame-layer bit allocation for multi-view video coding based on frame complexity estimation

“…As a result, the above scheme generally induces skipped frame and quality degradation. Ribas and Lei [17] proposed an optimal bit allocation scheme based on the residual energy for the coding frame as follows:…”

Adaptive bit allocation scheme for rate control in high efficiency video coding with initial quantization parameter determination

“…Nevertheless, due to the time-consuming multipass procedure, it is more appropriate for off-line applications. Other RC algorithms, such as [8][9][10], perform bit allocation according to the video texture complexity. Its basic idea is that each basic unit with higher texture complexity can be allocated more bits; whereas, each basic unit with lower texture complexity may be allocated fewer bits.…”