An efficient biprediction decision scheme of high efficiency video coding (HEVC) is proposed for fast-encoding applications. For low-delay video applications, bidirectional prediction can be used to increase compression performance efficiently with previous reference frames. However, at the same time, the computational complexity of the HEVC encoder is significantly increased due to the additional biprediction search. Although a some research has attempted to reduce this complexity, whether the prediction is strongly related to both motion complexity and prediction modes in a coding unit has not yet been investigated. A method that avoids most compression-inefficient search points is proposed so that the computational complexity of the motion estimation process can be dramatically decreased. To determine if biprediction is critical, the proposed method exploits the stochastic correlation of the context of prediction units (PUs): the direction of a PU and the accuracy of a motion vector. Through experimental results, the proposed method showed that the time complexity of biprediction can be reduced to 30% on average, outperforming existing methods in view of encoding time, number of function calls, and memory access.
The adaption of EUVL requires the development of new cleaning method for the removal of new contaminant without
surface damage. One of the harsh contaminants is the carbon contamination generated during EUV exposure. This highly
dense organic contaminant is hardly removed by conventional SPM solution on Ru capped Mo/Si multilayer. The
hopeful candidate for this removal is ozonated water (DIO3), which is not only well-known strong oxidizer but also
environmentally friendly solution. However, this solution might cause some damage to the Ru capping layer mostly
depending on its concentration. For these reasons, DIO3 cleaning solutions, which are generated with various additive
gases, were characterized to understand the correlation between DIO3 concentration and damages on 2.5 nm thick
ruthenium (Ru) surface. An optimized DIO3 generation method and cleaning condition were developed with reduced
surface damage. These phenomena were explained by electrochemical reaction.
A new dry cleaning methodology named laser-induced shock cleaning has been applied to remove the chemical-mechanical polishing (CMP) slurries from silicon wafer surfaces. After CMP process using the slurries, the slurry particles should be removed from the surface in order to avoid the circuit failure and enhance the yield. The well-distributed remaining silica particles were attempted to remove from the surface by using laser-induced plasma shock waves. In order to evaluate the cleaning performance quantitatively, the number of particles on the wafer surfaces were measured by surface scanner before and after cleaning. It was found that most of the silica particles on the wafer surface were removed after the treatment of laser-induced shock waves. The average removal efficiency of the particles was 99% over. It was found that cleaning performance is strongly dependent on a gap distance between laser focus and the surface and a suitable control of the gap is crucial for the successful removal of the particles.