33results about How to "Reduced prediction residuals" patented technology

The invention relates to a vehicle object multi-level knowledge dictionary construction method for monitoring video compression, which is used for expressing and compressing objects in a monitoring video, and comprises the following steps of extracting texture layer knowledge which comprises common textures of different types of vehicles in a multi-source monitoring video, and modeling the texturelayer knowledge by using a texture dictionary; extracting structural layer knowledge which comprises a common structure of the same type of vehicles, and modeling the structural layer knowledge by using a three-dimensional model; and extracting the personalized layer knowledge, wherein the personalized layer knowledge comprises transient knowledge that a certain vehicle individual keeps stable for a period of time, and using a residual dictionary to model the vehicle individual. According to the method, the multi-level knowledge dictionary of the object is established from the three levels ofthe texture layer, the structure layer and the personality layer, the appearance of the moving object in the image in the complex environment can be better expressed, the information such as edge details is richer, the tracking recognition efficiency of the monitored vehicle can be improved, and the method can be widely applied to the aspects of intelligent transportation and the like.

The invention discloses a filtering method for intra-frame prediction. The intra-frame prediction filtering method includes: obtaining filtering parameters; wherein, the filtering parameters include at least one of filtering reference pixels, filtering reference values, filtering ranges, and filtering coefficients; using the filtering parameters to filter the current intra-frame prediction block . Through the above method, the present invention can adjust the filtering method according to the actual situation of the intra-frame prediction block, and select the most effective filtering method for different intra-frame prediction blocks.

The invention discloses an intraframe prediction performance improvement encoding method. According to the method, prediction sample values are generated by use of mixed four-tap interpolation filtering, including DCT-based interpolation filtering and Gauss interpolation filtering, and for different prediction unit blocks, types of used interpolation filters are determined according to a given threshold; angle prediction mode classification is performed, i.e., intraframe angle prediction modes are classified into three types for carrying out different encoding processing; and boundary prediction sample smooth filtering is performed, i.e., final encoding prediction signals are generated by filtering boundary column or boundary row samples of prediction blocks by use of pixel differences between reference samples. According to the invention, through combination of direction features of intraframe angle prediction and space correlation of the reference samples, the generation process of the prediction signals is optimized, the prediction precision is improved, and better encoding compression performance is obtained.

The invention discloses a prediction-based three-dimensional mesh coding method. In the method, when predicting a normal vector texture image, the relativity between a geometry image and the normal vector texture image and the relativity among three components of the normal vector texture image are fully considered, the quality of the predicted normal vector texture image is high, and thus the predicted residual is small, which facilitates coding and transmission; and the quality of the decoded normal vector texture image is improved greatly, a third-dimension effect of the reconstructed three-dimensional mesh model is upgraded, and users can get excellent visual experience.