AVS-S Coding Based on Background Model

doi:10.12068/j.issn.1005-3026.2021.01.005

Abstract

Abstract: In order to improve the coding efficiency of surveillance video， a new background frame update method was proposed， namely， iterative update mean value method， under the coding framework of AVS surveillance extension grade. The nature of the pixel in a certain frame was determined according to the principle of different frequencies of occurrence of a certain pixel in the foreground area and in the background area. Through the test comparison of the surveillance video Crossroad， Overbridge and Classover， the pixel values of the background model corresponding to the pixels of different nature were obtained. The results showed that the shortcomings that slow moving objects are difficult to eliminate from the background are improved to a certain extent in this experiment. At the same time， the integrity of the background information is strengthened and the quality of the background frame is improved. Under the conditions of the same bit rate and the same peak signal-to-noise ratio， compared with the AVS benchmark method， the average code saving rate is 43.283% and the peak signal-to-noise ratio is increased by 1.186dB on average. The coding efficiency of its surveillance video is also improved.

Key words: background frame update method; background model; surveillance video; monitoring the AVS stretch grade; AVS benchmark grade

CLC Number:

TN919.81

SANG Ai-jun， YU Huan， ZHANG Han-yu. AVS-S Coding Based on Background Model[J]. Journal of Northeastern University(Natural Science), 2021, 42(1): 31-36.

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