Информационно-управляющие системы / №2 2017

OPTIMIZATION OF ERROR CONCEALMENT BASED ON ANALYSIS OF FADING TYPES Part 2: Modified and New Models of Video Signal Error Concealment. Practical Simulations and their Results (160,00 руб.)

Первый автор	Hadar Ofer
Авторы	Bronfman Irina , Blaunstein Nathan
Страниц	10

160,00р

ID	596820
Аннотация	Purpose: This work is based on the recent research investigations in the combination of two subjects: Fading and Error Concealment. The main aim of the work is to present a more effective method of calculations of fading channel's parameters and to devise methods of achieving of better and more effective performance of Error Concealment, which will lead to higher quality of the video signals after passing through the fading channel. Methods: We explore the influence of fading on a communication channel, by studying the Gaussian, Gaussian, and Ricean distributions. Additionally, we explore existing methods of prediction and of Error Concealment and their influence on the video quality after its exit from the fading channel. Results: It is demonstrated that the Ricean distribution is broader and that it includes the other distributions, Gaussian (ideal channel) and Rayleigh (channel with a strong fading). Therefore, this distribution is used for tests of practical cases occurring in the video channel. On the issue of Error Concealment, a method of Symmetrical CALIC which is an optimization of the CALIC method, was implemented and compared with the original CALIC and with other methods. It has been determined that the proposed optimization yields better results than all the methods used for comparison. In addition, a new method of Error Concealment, named Balanced Percentage Calculation, is proposed. In comparison, its results are two times better on average than the results of Symmetrical CALIC, and are much better than the results of other methods used. Two themes have been combined in such a way that fading influenced the appearance of errors in the video. Those errors have been replacedиby the proposed methods of Error Concealment. All practical tests and comparisons were performed using the MatLab. Practical relevance: The proposed method of calculations of fading channel's parameters allows to perform calculations for all types of channels. This method significantly facilitates work with channels in general and with necessary calculations for channels in particular. The suggested optimization of the existing method of Error Concealment and the new proposed method of Error Concealment allow to receive higher quality video after passing through the fading channel.

Hadar, O. OPTIMIZATION OF ERROR CONCEALMENT BASED ON ANALYSIS OF FADING TYPES Part 2: Modified and New Models of Video Signal Error Concealment. Practical Simulations and their Results / O. Hadar, I. Bronfman, N. Blaunstein // Информационно-управляющие системы .— 2017 .— №2 .— URL: https://rucont.ru/efd/596820 (дата обращения: 20.04.2024)

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We propose using symmetric known information — rows and columns surrounding a lost block. <...> In this case, lost pixels “get” more information and may be recovered more accurately. <...> The offered method is called Symmetrical CALIC. <...> Both these methods function simultaneously from the four sides of the lost block. <...> The first pixels (angular) are predicted based only on known pixel around lost block, and other pixels are predicted based on known and earlier predicted pixels. e se ee The Simulation Algorithm H.264 is a modern video format. <...> Videos in this format are used to test the proposed methods of EC and their analysis. <...> The algorithm for calculating each pixel from missed block is presented in Section “The Simulation Algorithm” and the results of this method are presented in Section “Results of Computation”. <...> We propose a model based only on two Channal Parameters LCR calculating  Fig. 3. <...> Thereafter, for all possible combinations of these parameters, LCR and BER are calculated using the formulas (22), (33) (see Part 1). <...> Inside the channel a randomly picked BER value for Ricean fading (for K1) is selected. <...> This BER value represents the number of lost bits in each frame. <...> Then, depending on the number of bits per pixel, the number of lost pixels is calculated for each frame. <...> In H.264 video format, during the passage of the video through the channel, the blocks that are lost consist mostly of 4 4 pixels. <...> Therefore, by dividing the previously calculated number of lost pixels by 16 pixels per block, the number of lost blocks in each frame is obtained. <...> The gradient of intensity function at the current pixel I is estimated by computing the following quantities: 70 ИНФОРМАЦИОННОУПРАВЛЯЮЩИЕ СИСТЕМЫ for prediction the pixel   % weak vertical edge       ;   weak horizontal edge         ;  } After the angular pixels have been predicted (concealed), prediction of the following pixels, P2, P6, P10, P14, is simultaneously performed, based on the known and earlier predicted pixels. <...> The fragment is characterized by medium and slow speed movement, by shifting background, and by the presence of details ranging from large to small. <...> Video 2 Technical characteristics: Data rate: 371 kbps Total bit rate <...>

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