An Adapted Intra and Inter Prediction Algorithm for H.264

2015 ◽  
Vol 740 ◽  
pp. 830-833
Author(s):  
Yue Yue Wang ◽  
Yu Bin Cui
Keyword(s):  
Selection Criteria ◽  
Mode Selection ◽  
Selection Method ◽  
Prediction Algorithm ◽  
The Novel ◽  
Inter Prediction ◽  
Integer Transform ◽  
Transform Coefficients ◽  
Residual Block

An adapted prediction algorithm for H.264 is proposed in this paper. For I frames, a new intra algorithm is proposed in which a novel Intra_4×4 mode selection method is designed. Nine Intra_4×4 modes are divided into three classes, the suitable mode class for current 4×4-block is predicted using the mode classes of neighboring left and up blocks. For inter frames, a new inter prediction algorithm is proposed, and two matrixes which are composed of sum of absolute values of the integer transform coefficients in 4×4-residual-block contained in luminance 16×16-block and 8×8-block are defined respectively, the novel MB and sub-MB mode selection criteria which use the derived gradients of the two matrixes are then proposed.

The Research on Port Logistics Mode and the Selection

2014 ◽  
Vol 945-949 ◽  
pp. 3209-3218
Author(s):  
Dong Quan Sun ◽  
Yong Yang
Keyword(s):  
Mode Selection ◽  
Selection Method ◽  
Development Mode ◽  
Port Development ◽  
Factors Influencing ◽  
Port Logistics ◽  
Logistics Mode

According to the characteristics and trends of our country port development, and the port logistics development mode, and to determine the factors influencing the development of port logistics, and then study the reasonable mode selection method.

Improved Damage Location Accuracy Using Strain Energy-Based Mode Selection Criteria

AIAA Journal ◽  
10.2514/2.159 ◽  
1997 ◽  
Vol 35 (4) ◽  
pp. 693-699 ◽  
Author(s):  
Scott W. Doebling ◽  
Francois M. Hemez ◽  
Lee D. Peterson ◽  
Charbel Farhat
Keyword(s):  
Strain Energy ◽  
Selection Criteria ◽  
Mode Selection ◽  
Location Accuracy ◽  
Damage Location

Fuzzy Holoentropy-Based Adaptive Inter-Prediction Mode Selection for H.264 Video Coding

2019 ◽  
Vol 10 (2) ◽  
pp. 42-60
Author(s):  
Srinivas Bachu ◽  
N. Ramya Teja
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
Mode Selection ◽  
Rate Distortion ◽  
Computation Time ◽  
Exhaustive Search ◽  
Inter Prediction ◽  
Major Drawback ◽  
Prediction Mode

Due to the advancement of multimedia and its requirement of communication over the network, video compression has received much attention among the researchers. One of the popular video codings is scalable video coding, referred to as H.264/AVC standard. The major drawback in the H.264 is that it performs the exhaustive search over the interlayer prediction to gain the best rate-distortion performance. To reduce the computation overhead due to exhaustive search on mode prediction process, this paper presents a new technique for inter prediction mode selection based on the fuzzy holoentropy. This proposed scheme utilizes the pixel values and probabilistic distribution of pixel symbols to decide the mode. The adaptive mode selection is introduced here by analyzing the pixel values of the current block to be coded with those of a motion compensated reference block using fuzzy holoentropy. The adaptively selected mode decision can reduce the computation time without affecting the visual quality of frames. Experimentation of the proposed scheme is evaluated by utilizing five videos, and from the analysis, it is evident that proposed scheme has overall high performance with values of 41.367 dB and 0.992 for PSNR and SSIM respectively.

scholarly journals Comparing the Performance of Algorithm with Relevant Features for Histological Categorization of Lung Cancer

2021 ◽  
Vol 12 (2) ◽  
pp. 357-363
Author(s):  
V. NishaJenipher , Et. al.
Keyword(s):  
Lung Cancer ◽  
Selection Process ◽  
Feature Selection Method ◽  
Wrf Model ◽  
Selection Method ◽  
Classification Algorithm ◽  
Prediction Algorithm ◽  
Long Period ◽  
The World ◽  
Performance Of Algorithm

Due to increasing cancer cases around the world, Lung cancer has become the favorite topic of research for a long period of time. The actual reason is due to the increasing rate of new cases across the globe. Therefore, many researchers used prediction or classification algorithm to identify the factors that contribute to the increase of this deadly disease. Two models were built namely WRF and RF. RF model provides the result of features selected by a predominant feature selection method whereas WRF model provides result of all features without performing any selection process. A comparison is made to inform the importance of selecting the feature for classification or prediction algorithm. The accuracy provided by WRF model is higher than RF model which highlights the importance of selecting the feature for classification algorithm.  

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