Evolutionary strategy based improved motion estimation technique for H.264 video coding

In this paper we propose an improved motion estimation algorithm based on evolutionary strategy (ES) for H.264 video codec applied to video. The proposed technique works in a parallel local search for macroblocks. For this purpose (mu+lambda) ES is used with an initial population of heuristically and randomly generated motion vectors. Experimental results show that the proposed scheme can reduce the computational complexity up to 50% of the motion estimation algorithm used in the H.264 reference codec at the same picture quality. Therefore, the proposed algorithm provides a significant improvement in motion estimation in the H.264 video codec

Soil Morphological Properties Of Planted Mono And Mixed Tree Species At Gunung Apeng National Park, Sarawak

Reforestation and effective soil conservation management is required to restore and manage degraded forest land in tropics. Information regarding the soil characteristics in forest land is essential as a guide in future reforestation programme. The differences in soil characteristics are usually attributed to differences in environmental factors such as topography, runoff and tree species planted which affect the soil genesis (Tamai, 2010). Hence, assessment of soil characteristics such as soil morphological properties is important to determine the condition of the soils in forest areas. Soil morphological on a given land can be determined by observing the soil profile of the different soil horizon. During in-situ observation, the interpretation of soil can show various soil attributes. In this study, assessment on the soil morphological properties of reforested areas planted with different tree species of mono and mixed species planting was conducted. Hence, obtaining the status of the soil condition in the study area is essential in order to determine the suitability of the selected tree species and the planting technique in order to achieve the most productive level in terms of its growth and performance

Evolutionary strategy based improved motion estimation technique for H.264 video coding

In this paper we propose an improved motion estimation algorithm based on Evolutionary strategy (ES) for H.264 video codec applied to video. The proposed technique works in a parallel local search for macroblocks. For this purpose (mu+lambda) ES is used with an initial population of heuristically and randomly generated motion vectors. Experimental results show that the proposed scheme can reduce the computational complexity up to 50% of the motion estimation algorithm used in the H.264 reference codec at the same picture quality. Therefore, the proposed algorithm provides a significant improvement in motion estimation in the H.264 video codec