The drawbacks of the existing algorithms for coding data of video information resources in the aero monitoring system are analyzed. The main ones are: the complexity of the algorithmic implementation; loss of informative data that determine the semantic component (carry semantic load) of the information resource. To solve these problems, a model for transforming the alphabet of encoded data is being developed. The essence of the developed model is to determine and take into account the significance of the elements of the encoded data. The significance of message elements means taking into account the probabilistic distribution of elements in the message and the structural features of the color model to which the initial data is presented. Experimental studies are being carried out to confirm the adequacy of the developed model. The effectiveness of the developed model is assessed from the standpoint of ensuring the reduction of the power of the alphabet of the encoded data, provided that the high quality of video images is ensured. The directions of further research are determined, which involve the synthesis of the developed model with technologies for coding data information resources without losses. transformation, information resource data, redundancy, significance, coding, aeromonitoring ORCID: 0000-0001-6216-3006 (S. Khmelevskiy); 0000-0001-6806-4914 (I. Tupitsya); 0000-0001-6062-7743 (M. Parkhomenko); 0000-
In the system of information support of departmental bodies, a rather important role is assigned to
the use of the aero segment [
Accordingly, the requirements for the video information resource are increasing. The main ones
among them [
The analysis of the latest scientific research indicates that the existing compression technologies
are built on the principle of multilevel processing (they assume the implementation of step-by-step
data processing) [
2022 Copyright for this paper by its authors. data processing. All subsequent stages (preparation for encoding and encoding, respectively) are associated with the processing of intermediate data. And accordingly, an increase in the number of processing stages implies an increase in the complexity of the algorithmic implementation (which increases the time for data processing) and a decrease in the quality of the restored images.
Therefore, it is proposed to use an approach to ensure the required level of video image quality under conditions of limited bandwidth of data transmission channels, the essence of which is to transform the original alphabet of the encoded data in the direction of reducing psycho-visual redundancy by determining the significance of the encoded data elements.
Thus, the purpose of the article is to develop a model for transforming the alphabet of encoded data to ensure the required level of video image quality in conditions of limited bandwidth of data transmission channels in aero monitoring systems. 2. Development of a transformation model for the alphabet of encoded data to ensure the required level of video image quality in aeromonitoring systems
It is proposed to develop a model for transforming the alphabet of the encoded data, which will take into account the significance of the encoded elements according to some quantitative criterion the sign of the element's significance. So for the message, which is given by the following expression: where xi - i - th message element X(n) , i 1, n , message alphabet X(n) will look like this: X(n) {x1; ...;xi ; ...;x n } , i 1, n ,
X(m) {x1; ...;xi ; ...;x m} , i 1, m , RGB color space with the size 3 , i.e.:
VRGB 3 , where VRGB - the volume of the cube in the RGB color model; - the length of the side of the cube, in pixels.
To assess the significance of elements xi messages X(n) it is proposed to use a quantitative feature, which is given by the following expression: where m - the number of elements in the alphabet X(m) messages X(n) , i 1, m .
Taking into account the fact that at the initial stage the encoded data is represented using the RGB model, that is, they are elements of an RGB cube, the elements of the encoded data can be represented as follows:
xi xi (xiR , xiG , xiB ) , where xiR - the component red of the element xi ; xiG - the component green element xi ; xiB the component blue of the element xi .
It is proposed to transform the alphabet of the encoded data in several stages (Fig. 1). At the first stage, the elements are determined xi messages X(n) , which do not have a significant impact on the semantic component of the message, that is, psycho-visual redundancy is eliminated. At this stage, the probability distribution law is determined P(x i ) appearance of elements xi in the message X(n) .
1. At the next stage, the significance of the elements is determined xi messages X(n) quantitatively. To this end, the element xi messages X(n) represented as the center of a cube in the where S(xi ) - the coefficient of significance of the element xi messages X(n) ; P(x i ) - the probability of the item appearing xi in the message X(n) ; xi - message element X(n) , which is the center of the generated cube in the RGB color model; xij - elements of the formed color cube in the RGB model, xij xij (xijR , xijG , xijB) , j 1, , 3( 1) ; D(xi , xij ) - distance between element xi (the center of the formed cube) and elements xij the generated RGB cube.
Information resource data presented using the RGB color model
X(n) {x1;...; xi; ...; xn} xi xi (xiR , xiG , xiB), i 1, n X(m) {x1;...; xi;...; xm}, i 1, m
Transformation of the message and the alphabet of the encoded
data X(n) ftransf X(n)
X(n) {x1;...;xi;...;xn} xi ftransf (| Xtransf () |,S(xi)lim) xi xi, S(xi) S(xi)lim; xij, S(xi) S(xi)lim, S(xij) S(xi)lim.
xi S(xi )
Formation of a model for determining significance for message X(n)
elements xi Determination of the law of
probability distribution elements in the message
P(xi )
Defining an RGB cube
model VRGB 3
Determination of the optimal exponent
S(xi) P(xi) P(xi) j1 D(xi, xij)
D(xi , xij ) (xiR xijR )2 (xiG xijG )2 (xiB xijB )2 .
2. The third stage is the ranking of the data array (coefficients of significance S(xi ) elements xi messages X(n) ) from maximum to minimum value.
3. At the fourth stage, the significance threshold is determined S(xi )lim elements xi messages X(n) (image pixels). This indicator is determined by the power of the alphabet of the reconstructed message. Thus, taking into account the transformation of the alphabet X(m) initial data using the proposed approach message X(n) will take the following form:
X(n) f transf X(n) , X(n) {x1; ...;xi ; ...;xn } , where f transf (| X transf () |,S(xi )lim ) - function of forming a transformed message taking into account the threshold value of the significance coefficient S(xi )lim elements and power of the alphabet of the transformed message; xi - i - th element transformed message X(n) , i 1, n ;
X transf () - transformed message alphabet X(n) , which is formed taking into account the significance indicator; | X transf () | - the power of the alphabet of the transformed message X(n) . (6) (7) messages X(n) to form a transformed message X(n) . Given this information, based on the function f transf (| X transf () |,S(xi )lim ) items are ranked xi transformed message X(n) at a given level power | X transf () | alphabet X transf () transformed message X(n) . This is given by the following expression:
xi f transf (| X transf () |,S(xi )lim ) .
It should be noted that it is from the power | X transf () | alphabet X transf () transformed messages X(n) the degree of compression and, accordingly, the degree of distortion of the image elements depends. Thus, at the final stage, the formation of the alphabet takes place X transf ( ) transformed messages X(n) , the essence of which is to replace the elements xi original message X(n) for which the significance coefficient S(xi ) matters less than the threshold S(xi )lim , that is: elements of the alphabet Xtransf (m) for which the following condition is satisfied:
Thus, the process of forming a transformed message X(n) is given by the following expression system:
xi , S(xi ) S(xi )lim ; xi
xij , S(xi ) S(xi )lim , S(xij ) S(xi )lim .
In turn, the purpose of transforming the alphabet X(m) the encoded data is power reduction | X(m) | subject to the provision of high quality video images (in terms of using compression algorithms for coding data), i.e. the following condition must be met:
| X transf () || X(m) | . 3. Evaluation of the effectiveness of the developed model of transformation of the alphabet of encoded data from the standpoint of ensuring the required level of video image quality in aeromonitoring systems Analysis of transformations of the nature of the probability distribution law for the appearance of message elements as a result of clustering based on the number of series of units.
In order to determine the optimal values of quantitative indicators (RGB cube model - length sides of a cube, exponent ), which are used in the developed model of transformation of the alphabet X(m) coded data, it is proposed to conduct a number of experimental studies. To determine the effectiveness of the developed model for transforming the encoded data, a number of experiments were carried out. Highly saturated images were used as initial data; an example of one of them is shown in Fig. 2. The results of experimental studies to determine the optimal values of quantitative indicators that are used in the developed model of the transformation of the alphabet X(m) of the encoded data are shown in Figs. 3 - 4. Analysis of the results of experimental studies to determine the optimal values of quantitative indicators that are used in the developed model of transformation of the alphabet X(m) coded, which are presented in Fig. 3-4, indicate that:
1. The optimal value for the quantitative indicator of the RGB cube model is length side of the cube is as follows (Fig. 3): 9 .
S(xi ) S(xi )lim , S(xi ) S(xi )lim . (8) (9) (10) (11)
This is due to the fact that for a given value of the length side of the cube, the minimum standard deviation is provided, which has the following value (Fig. 3):
CKO CKO min 0,7% .
It should be noted that this RGB cube model (with 9 ) is selected taking into account the assessment of the complexity of the algorithmic implementation of the developed model for transforming the encoded data (Fig. 4).
2. Analysis of the dependence of the standard deviation on the length sides of a cube for different values of the exponent (Fig. 4) indicates that for the developed model of transformation of the alphabet of encoded data with the optimal value of the indicator is the following:
Taking into account the results of the experimental studies (data from expressions (11) - (12)), expression (5) takes the following form:
At 3,5 the standard deviation is provided, which has the following value (Fig. 4): 3,5 .
CKO 0,7 % .
S(xi ) .
| X(m) | | Xtransf () | 9,55.
Further, it is proposed to evaluate the effectiveness of the developed model from the standpoint of ensuring power reduction | X(m) | alphabet X(m) of the encoded data, provided that the high quality of video images is ensured, that is, the condition specified by expression (10) is met. So for the tested image, which was used in the course of experimental studies, the result of applying the developed model for transforming the alphabet of the encoded data is a decrease in the power of the alphabet by approximately 10 times (Fig. 5):
Thus, we can conclude that the proposed model for transforming the alphabet of the encoded data allows to ensure not only the high quality of reconstructed images, but also to create more favorable conditions for the further use of lossless compression coding technologies in order to compactly represent the data of the information resource. Therefore, the goal of further research is to synthesize the developed model for transforming the alphabet with technologies for compact representation of (12) (13) encoded data without loss to increase the efficiency of delivery of data information resources while ensuring the required level of quality.
0 5 7 3,8
10 6,6 3,4 6,2 3 15 5,8 2,6 20 5,4 2,2 5 1,8 25 4,6 1,4
Thus, the developed model makes it possible to ensure a sufficiently high quality of encoded data ( CKO 0,7 % ) by transforming the alphabet of the message. The essence of which is to additionally eliminate the psycho-visual redundancy of the information resource data by determining the significance of the elements in the message. The significance of the elements of the message is understood as taking into account both the law of the probabilistic distribution of elements in the message and the structural features of the color model to which the initial data are presented. This makes it possible to reduce the power of the alphabet of the encoded data by almost 10 times, which, in turn, makes it possible to create more favorable conditions for increasing the efficiency of video data encoding from the standpoint of ensuring the required level of quality in conditions of limited bandwidth of the data transmission channel.
3500|0X(m) | 30000 25000 20000 15000 10000 5000 0 29317
3070 RGB
PM