**3.2 Initial grid search**

In [19], Liquan et al. have proposed a fast mode decision algorithm by skipping some depths. The proposed work allows saving about 21.5% of encoding time with a slight bitrate increase and a negligible efficiency loss coding. The algorithm proposed by Qin [20] uses the ECU algorithm according to an adaptive MSE threshold value. This work ensures time saving without degradation in the quality. Podder [21] has also proposed an interesting software method to reduce the ME time. Based on human visual features (HVF), an efficient decision of the appropriate block partitioning mode has been obtained. This work allows saving 41.44% of the execution time for SCVS video sequences. In the work published in [22], a fast HEVC ME based on DS and three fast mode decisions, ECU, ESD, and CBF modes, have been presented. Simulation results show a reduction of 56.75% in the complexity of HEVC in terms of execution time, accompanied with slight degradation in video quality and bitrate, when comparing the HM.16.2 executed on an Intel® Core TM i7–3770 @3.4 GHz processor. Authors in [22] have tested just one sequence from each class with just two quantification parameters (QPs), QP = 22 and 37, to

By analyzing all these previous works, we can note that using fast mode decision algorithms represents an interesting technique in order to reduce the HEVC com-

TZ Search algorithm, used in HEVC ME process (**Figure 3**), includes four

These stages, which are the motion vector prediction (MVP), the first search performed with a pattern of square or diamond forms, the refinement, and the

To compute the corresponding block's median predictor, the TZS algorithm uses

the up predictor, the upper right predictor, and the left predictor (**Figure 4**).

**3. Overview of the motion estimation in the new HEVC**

distinct main stages in order to determine the best motion vector.

raster search, are described in the next subsections.

**3.1 Motion vector prediction (MVP)**

evaluate the use of the fast modes.

putational complexity.

*Digital Imaging*

**Figure 3.**

**14**

*Motion estimation process.*

The first search is performed by the determination of the search pattern and the "searchrange." As it is detailed in **Figure 5(a)** and **(b)**, the main goal of this stage is to localize the search window via a pattern of square or a diamond forms.

Thus, these two search patterns are referred to the eight points for each round. The distance corresponding to the minimum distortion point is saved in the "BestDistance" variable. Currently, diamond search pattern is used as default, but the square pattern search can also be used by modifying the HEVC configuration file through the "Diamondsearch" variable.

**Figure 4.** *MV adjacent of a current PU.*

**Figure 5.**

*Diamond/square search pattern. (a) Diamond search pattern stride length equal to 4. (b) Square search pattern stride length equal to 4.*
