Miryem Hrarti

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Statistical methodologies are the main tools used in video compression and this lead to a kind of stagnation in terms of performance. This means that solutions for increasing the visual performance of video compression have to come from other fields like the perception. One can notice that coding errors in highly textured areas are relatively less(More)
In the frame-level rate control algorithm of H.264/AVC baseline profile, the Quantization Parameter (QP) is determined according to a target bit-rate estimated by the bit allocation process and a frame complexity measure. The target bits calculation process assumes similar characteristics for all frames and for a single frame on the whole set; the Mean(More)
This paper aims to improve H.264 bit-rate control. The proposed algorithm is based on a new and efficient Rate-Quantization (R-Q) model for the intra frame. For the inter frame, we propose to replace the current use of MAD by a new MAD-based human Contrast Sensitivity (MAD-CS) which is a more accurate complexity measure. R-Q model for the intra frame(More)
Video encoding rate control has been the research focus in the recent years. The existing rate control algorithms use Rate-Distortion (R-D) or Rate-Quantization (R-Q) models. These latter assume that the enhancement of the bit allocation process, the quantization parameter determination and the buffer management are essentially based on the improvement of(More)
Rate control plays a key role in video coding standards. Its goal is to achieve a good quality at a given target bit-rate. In H.264/AVC, rate control algorithm for both Intra and Inter-frames suffers from some defects. In the Intra-frame rate control, the initial quantization parameter (QP) is mainly adjusted according to a global target bit-rate and length(More)
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