KR100954303B1 - spatial resolution control system for video applications and transmission control method for video applications using the spatial resolution control system - Google Patents

Abstract

The present invention relates to a spatial resolution control system of an image and an image transmission control method using the same.

According to the present invention, in transmitting an image, a total quality criterion in consideration of image quality and power consumption is set, and an optimal spatial resolution is calculated according to the total quality criterion. It is reduced and transmitted, and the receiving end recovers the reduced frame to its original size and displays it. As such, when the original image is reduced and transmitted to a predetermined size according to the total quality standard considering the image quality and power consumption, the image quality at the receiving end is higher than that of the conventional method of increasing the compression rate while maintaining the image size. It is excellent, and the decoding time is reduced, which greatly reduces the power consumption.

Quantization Coefficient, Bit Rate, Spatial Resolution, PSNR, Image Quality

Description

Spatial resolution control system for video applications and transmission control method for video applications using the spatial resolution control system

The present invention relates to a spatial resolution control system of an image and an image transmission control method using the same, and more particularly, to a spatial resolution control system of an image for preventing degradation of image quality at the receiving end and minimizing power consumption during image transmission. And an image transmission control method using the same.

Due to the remarkable development of communication technology, transmission / reception and storage of video information using a network have become an indispensable life item in modern society.

In particular, recently, thanks to the UCC craze, more diverse and unique videos can be easily accessed on the network.

However, the capacity of the use network supporting such video service is limited. Therefore, in order to increase the transmission / reception and storage efficiency of image information, it is very important to introduce an image compression technology so that an optimum image quality can be obtained within the capacity limit of a given network.

Typically, the video stream of a video service can be compressed by adjusting three factors: temporal resolution, spatial resolution and image quality. That is, given the temporal and spatial resolution, the video encoder adjusts the image quality by adjusting the quantization coefficients to reach a specified bit rate.

However, the larger the motion and the greater the complexity of the scene, the greater the amount of data. In particular, in the case of a video service, the change in the motion of the video and the complexity of the video vary, so that the variation in the bit rate output through the video encoder becomes severe.

Moreover, fluctuations in the output bit rate are even worse due to limited network capacity and limited buffer capacity of the encoder and decoder.

Therefore, in order to minimize such a bit rate variation, when the image is switched, the complexity of the image to be encoded is predicted in advance based on the current buffer state and statistical data of previously encoded images, and then the quantization coefficient is determined. A bit-rate control technique is used in which the quantization coefficients are up-adjusted and coded up a few steps.

However, when the quantization coefficient is adjusted upward, more data is discarded during the compression process, thereby making the bit stream more compact, but the quality of the image is degraded due to the low bit rate.

In addition, when the scene transition occurs when the quantization coefficient is already set to the higher coefficient and the higher quantization coefficient is encoded, the quality degradation of the next video becomes more severe.

In addition, when the compression rate is adjusted by adjusting the quantization coefficient in the low bandwidth state, the image quality is further degraded due to excessive data compression and information loss. In particular, video transmission through a wireless LAN or a mobile phone is performed. In the wireless communication of this quality degradation appears to be more severe.

On the other hand, when transmitting a video, if the bit rate is increased by pursuing only the video quality, the decoding time increases, which means that the power consumption increases.

In particular, handheld devices such as DMB phones and mobile phones have a limited battery life. The energy consumption of the CMOS circuit constituting the CPU of the handheld device can be written as follows.

E ∝ CV ²

Where C is the effective switching capacitance in operation, V is the supply voltage and f is the clock frequency.

Thus, the CMOS circuit in the CPU consumes less energy when operating at lower frequencies, thereby reducing the supply voltage.

However, for multimedia products, the CPU frequency is required to be high enough to accurately decode and display the compressed video. And in order to find the lowest appropriate CPU frequency, the video decoder must be able to predict how the runtime required to decode one picture frame is affected.

Therefore, increasing the bit rate in video transmission may be advantageous in terms of video quality, but the power consumption is increased due to the increased decoding time, and thus, especially in a handheld device using a limited-use battery as a power source. It is a weak point.

SUMMARY OF THE INVENTION An object of the present invention is to provide a spatial resolution control system of an image and an image transmission control method using the same, which can prevent degradation of quality due to excessive data compression and information loss. have.

Another object of the present invention is to provide a system for controlling spatial resolution of an image and minimizing power consumption due to an increase in decoding time and an image transmission control method using the same.

In order to achieve the above objects, a spatial resolution control system for an image according to the present invention calculates an optimal spatial resolution according to a total quality criterion in consideration of image quality and power consumption, and has an image frame size to have the calculated spatial resolution. It is characterized by transmitting by adjusting.

In addition, the spatial resolution control system of the image according to the present invention for achieving the above object, the network monitor for monitoring the network state to transmit the image, the bandwidth detection unit for detecting the available bandwidth, the total considering the image quality and power consumption According to the quality standard, the spatial resolution selecting unit selects an optimal spatial resolution that improves image quality and obtains power saving effect, and adjusts the size of the original image frame to have an optimal spatial resolution selected from the spatial resolution selecting unit. And a parameter adjusting unit for adjusting a parameter required for selecting an optimal spatial resolution.

In addition, the image transmission control method according to the present invention for achieving the above object, the step of calculating the optimal spatial resolution according to the total quality standard in consideration of the image quality and power consumption, and the image to have the calculated spatial resolution And transmitting the adjusted frame size.

In addition, the image transmission control method according to the present invention for achieving the above object, the step of monitoring the network state to transmit the image, detecting the bandwidth available for the image transmission, the image quality and power consumption According to the total quality criteria considered, after selecting the optimal spatial resolution to improve the image quality at the receiving end to receive the image, and to reduce the power consumption, the frame of the image to have the selected optimal spatial resolution Transmitting the image to the receiving end by adjusting the size; and receiving the reduced image from the receiving end, resizing the image to its original size, and displaying the same.

In this case, the optimal spatial resolution is the relationship between the bit rate and distortion (distortion) of the image, the peak signal (PSNR) for the noise ratio, the time required to decode the video frame, and the resizing of the reduced image to its original size. It is selected according to the total quality measurement standard extracted by considering all the time.

According to the present invention, in transmitting an image, a total quality criterion in consideration of image quality and power consumption is set, and an optimal spatial resolution is calculated according to the total quality criterion. It reduces and transmits the data, and the receiving end restores and displays the reduced video frame to its original size. As a result, it is possible to further improve the image quality at the receiving end, and to reduce the decoding time, thereby significantly reducing power consumption, compared with the conventional case of transmitting by increasing the data compression rate while maintaining the image frame size. do.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The present invention relates to a spatial resolution control system of an image and an image transmission control method using the same. The present invention proposes a spatial resolution control system of an image and an image transmission control method using the same to prevent power consumption and reduce power consumption.

1 is a block diagram of a spatial resolution control system of an image according to the present invention.

Referring to FIG. 1, the spatial resolution control system 100 may include a network monitor 102 that monitors a network state to transmit an image, a bandwidth detector 104 that detects available bandwidth, and improves image quality. A spatial resolution selecting unit 106 for selecting an optimal spatial resolution capable of obtaining a saving effect, and a frame reduction unit for reducing the size of the original image frame to have an optimal spatial resolution selected from the spatial resolution selecting unit 106 ( 108) and a parameter adjusting unit 110 for adjusting parameters necessary for selecting an optimal spatial resolution.

In this case, the spatial resolution selecting unit 106 determines the peak signal PSNR and the time required for decoding the video frame with respect to the noise ratio derived from the relationship between the bit rate and distortion (distortion) of the image. According to the total quality measurement standard, the optimal spatial resolution is selected to reduce the power consumption while improving the image quality.

As such, when an image is input to the spatial resolution control system 100, the spatial resolution control system 100 reduces the input image to a spatial resolution that can reduce power consumption while improving the quality, and then returns to the receiving end. send.

By resizing and displaying the reduced-sized image in its original size, the receiving end can easily enjoy an image having good image quality while minimizing power loss of the image display apparatus possessed by the user.

2 illustrates an image transmission control method performed by the spatial resolution control system of the image illustrated in FIG. 1.

Referring to Figure 2, first, to monitor the network state to transmit the image (200).

Subsequently, the bandwidth available for video transmission is detected (202), and then the optimal spatial resolution for improving the video quality at the receiving end and obtaining power saving effect is selected (204).

Subsequently, the frame size of the image is reduced to have the optimal spatial resolution and then transmitted to the receiving end (206).

Then, the receiving end receives the reduced image and resizes it to its original size and displays it (208).

In the above video transmission control method, the optimal spatial resolution is the relationship between the bit rate and distortion (distortion) of the image, the peak signal (PSNR) for the noise ratio, the time required to decode the video frame, and the reduced image. The total quality measurement standard is selected in consideration of all the time required for resizing to the original size. The process of extracting the total quality measurement standard is described in detail with reference to the following equations and drawings. Let's look at it.

First, FIG. 3 is a graph showing the relationship between the bit rate and the image quality, where the x axis represents the bit rate and the y axis represents the peak signal PSNR for a noise ratio that may be related to the image quality.

As shown in FIG. 3, as the bit rate increases, the PSNR increases. The relationship between the bit rate and the PSNR may be derived by the following equations.

First, if the relationship between the bit rate and distortion (distortion) of the image is defined based on the quantization theory, it can be expressed as, for example, the following equation (1).

Where D is a distortion measured in mean-square error (MSE), where the square of the difference between the original and reconstructed pixel data (square), R is the bit rate of the decoded bit stream, and σ _x ² is the input Indicates a change in the signal. If the above equation (1) is represented more generally, for example, it can be expressed as the following equation (2).

Where γ is the correlation coefficient of the data and ε _x ² is a scaling parameter whose source distribution is determined by Gaussian, Laplacian or uniform distribution.

However, a more practical measurement criterion for image quality can be expressed as a peak signal (PSNR) for a noise ratio that can be related to distortion (D), for example according to Equation (3) below.

These results indicate a linear relationship between picture quality and bit rate. However, if the distortion of the input source takes Laplacian, a square root model, for example, as in Equation 4 below can be proposed.

Where R is the bit rate and q1, q2 and q3 are constants that can be empirically inferred by experimentation or observation, depending on the particular coding method and video content.

As shown in FIG. 3 and Equations (1) to (4), the bit rate and the image quality of the image are linear, and as the bit rate increases, the image quality improves.

On the other hand, Figure 4 is a graph showing the change in decoding time for a single frame having a variety of spatial resolution, the x axis represents the bit rate, the y axis represents the decoding time.

4, lines L1, L2, L3, L4 and L5 are 352 × 288 (100%), 320 × 256 (80%), 288 × 240 (70%), 272 × 224 (60%), respectively. And 176 x 144 (25%) spatial resolution. Decoding time increases as the bit rate increases.

This relationship between bit rate and decoding time can be derived by the following equations.

The time required to decode the video frame can be represented by, for example, the following equation (5) by the number of macro blocks N _MB and the average time T _MB for macro block decoding.

Here, the T _MB can be divided into two parts. That is, the macroblock header processing, the time for optional enhancement, such as a motion vector decoding and the time required for the compulsory process for processing a macroblock including a motion compensation, and variable-length DCT coefficient decoding, inverse quantization and inverse DCT O _MB Can be divided into

Typically, the image quality is proportional to O _MB which is alternately proportional to the bit rate assigned to each macroblock. Therefore, Equation (5) can be represented again to have a constant a as shown in Equation (6) below.

Furthermore, in Equation (6), the N _MB is directly related to the spatial resolution by N _MB = (Sx × Sy) / 16 × 16, so that, for example, the intrinsic constant b as in Equation (7) It can be represented again as

Here, Sx and Sy are the number of pixels in the horizontal and vertical directions, for example, can be represented by Equation (8) below.

As described in FIG. 4 and Equations (5) to (8), it can be seen that the decoding time increases linearly as the bit rate increases.

5 is a graph illustrating a change in resizing time according to various spatial resolutions, in which the x axis represents a bit rate and the y axis represents a resizing time.

Referring to Figure 5, lines L1, L2, L3, L4 and L5 are 352 × 288 (100%), 320 × 256 (80%), 288 × 240 (70%), 272 × 224 (60%), respectively. And a spatial resolution of 176 x 144 (25%).

Since the line L1 transmits the frame size of the image as it is, the resizing time is zero. In addition, the resizing time for displaying the decoded image due to the resizing overhead is somewhat unclear for various spatial resolutions.

Accordingly, when the final equation for the bit rate and the overall decoding time (decoding time + resizing time) is calculated by reflecting such resizing overhead, it can be expressed as Equation (9) including, for example, the display time constant t3. .

The relationship between the bit rate and the overall decoding time according to Equation (9) is shown in FIG.

6, lines L1, L2, L3, L4, and L5 are 352 × 288 (100%), 320 × 256 (80%), 288 × 240 (70%), 272 × 224 (60%), respectively. And 176 × 144 (25%) spatial resolution, and as the bit rate increases, the total decoding time combined with the decoding time and the resizing time increases.

As shown in FIG. 3 to FIG. 6, in transmitting video content, as the bit rate is increased, the image quality is improved and the decoding time is increased.

In this case, an increase in decoding time means an increase in power consumption. Therefore, increasing the bit rate may be advantageous in terms of image quality, but is a very disadvantageous condition in terms of power consumption. In particular, in the case of a handheld device using a limited-use battery as a power source, high power consumption is a very fatal disadvantage.

Accordingly, the present invention provides a spatial resolution control system of an image and an image transmission control method using the same to provide the best image quality under a given power supply level P and a bit rate R, and to reduce power consumption.

In Equation (10), a total quality standard of video content according to a change in image quality and energy is defined.

Here, φ is a total quality criterion in consideration of image quality and power consumption, Q represents image quality, and E represents energy, that is, power consumption required to achieve image quality.

With respect to Equation (10), as an additional change factor, w that reflects the user's interest in energy consumption may be further introduced and reconfigured as shown in Equation (11).

As shown in Equation (11), as the user's interest index w for energy consumption increases, the energy consumption can be reduced.

In addition, since energy and execution time can be exchanged, Q in Equation 11 above.

 And E can be expanded, for example, as shown in Equation (12) below.

Equation (12) may be represented by a function such as Equation (13).

Where R, S and w represent the bit rate, spatial resolution and energy interest index, respectively. Therefore, the total quality of the image can be calculated using the above R, S and w. For example, when the bit rate and the energy interest index are determined, the image quality depends on the spatial resolution, so that the spatial resolution corresponding to the best quality can be selected.

7 and 8 illustrate the relationship between the bit rate and the image quality for various spatial resolutions as experimental results of the Stefan sequence and the mobile sequence, respectively.

First, FIG. 7 shows the result of the Stefan sequence, where the x-axis represents the bit rate and the y-axis represents the PSNR. Lines L1, L2 and L3 show spatial resolutions of 352x288 (100%), 288x240 (70%) and 176x144 (25%), respectively.

In general, under the same bit rate conditions, the higher the spatial resolution, the more likely the PSNR also tends to increase. However, as shown in FIG. 7, it can be seen that the PSNR at a lower spatial resolution is rather excellent when the bit rate is below a certain value (below a specific bandwidth).

That is, the PSNR of the line L1 with the highest spatial resolution is the best when the bit rate is about 100kbps or more, but the PSNR of the line L2 with the spatial resolution of 288 × 240 (70%) is the highest when the bit rate is about 100 ~ 60kbps. It can be seen.

If the bit rate is about 60kbps or less, the spatial resolution is 176 × 144 (25%) compared to the line L1 with 352 × 288 (100%) or the line L2 with 288 × 240 (70%). It can be seen that the PSNR of the low line L3 is the highest.

Experimental results as shown in FIG. 7 can be similarly confirmed through FIG. 8.

8 shows the results according to the mobile sequence, where the x-axis represents the bit rate, the y-axis represents the PSNR, and L1, L2 and L3 are 352 × 288 (100%), 272 × 224 (60%) and 176 × 144 (25), respectively. %) Spatial resolution.

Referring to FIG. 8, that is, when the bit rate is about 110 kbps or more, the PSNR of the line L1 having the highest spatial resolution is the best, but when the bit rate is about 110 to 70 kbps, the line having the spatial resolution of 272 × 224 (60%) It can be seen that the PSNR of L2 is the highest.

If the bit rate is about 70 kbps or less, the spatial resolution is 176 × 144 (25%) compared to the line L1 with 352 × 288 (100%) or the line L2 with 272 × 224 (70%). It can be seen that the PSNR of the low line L3 is the highest.

Therefore, according to the experimental results in FIG. 7, when the bit rate is between about 100 and 60 kbps, it is preferable to reduce the spatial resolution to 288 x 240 (70%) for transmission in terms of image quality and power loss. If it is about 60 kbps or less, it is preferable to reduce the spatial resolution to 176 x 144 (25%) and to transmit the image quality and power loss.

In addition, according to the experimental results in FIG. 8, when the bit rate is about 110 to 70 kbps, it is preferable to reduce the spatial resolution to 272 x 224 (60%) for transmission in terms of image quality and power loss. In the case of 70 kbps or less, it is preferable in view of image quality and power loss of reducing the spatial resolution to 176 × 144 (25%).

Meanwhile, there is a need for a process of resizing the reduced frames to fit a predetermined display size. A resizing algorithm that upsamples the reduced frames to fit a given display size plays a very important role in the image resolution adjustment process according to the present invention. These resizing algorithms have been extensively studied by the image processing community, with a variety of algorithms ranging from simple multiplication to very complex computational results.

Such resizing can be performed, for example, by the following four methods.

First, method 0 is designed to support proportional reduction for extended space, using an integer-based 6-tap set derived from the Lanczos-3 filter. Thus, any scaling ratio is supported, which ratio can vary in the horizontal and vertical directions.

Method 1 only supports a pair of rescaling rates, where upsampling is realized by several pairs of stages.

Method 3 uses the three-lobed lanczos-windowed sinc function.

And method 4 uses a combination of an AVC half-sample filter and a bi-linear filter.

The PSNR and execution time of the resized image by the four resizing methods (method 0, method 1, method 3 and method 4) described above are shown in Table 1 below.

Resizing Method PSNR (db) Execution time (ms) 0 28.68 353 One 26.53 199 3 26.51 310 4 26.53 656

As can be seen from Table 1, Method 0 provides the best PSNR while the execution time is not higher than other methods. Thus, in resizing reduced frames, it is most desirable to apply the method 0 above.

9 and 10 show changes in total image quality for various bit rates as experimental results of the Stefan sequence and the Foreman sequence, respectively.

First, referring to FIG. 9, the x axis represents a bit rate, the y axis represents a total image quality, and L1, L2, L3, L4, and L5 represent 352 × 288 (100%), 320 × 256 (80%), and 288, respectively. 240 x 70 (70%), 272 x 224 (60%), and 176 x 144 (25%).

Here, the total image quality is a value calculated by considering all of w, which is an index of interest of users for PSNR, decoding time and resizing time, and energy consumption according to a bit rate change.

In general, under the condition of the same bit rate, the higher the spatial resolution, the more the total image quality tends to be improved. However, as shown in FIG. 9, when the bit rate is below a certain value, it can be seen that the total image quality at a lower spatial resolution is better.

That is, when the bit rate is about 120 or more, the total image quality of the lines L1 to L4 is excellent, but when the bit rate is about 120 kbps or less, the total image quality of the line L5 having the lowest spatial resolution is rather excellent.

Experimental results as shown in FIG. 9 can be confirmed in the same manner through FIG. 10.

Referring to FIG. 10, the x-axis represents the bit rate, the y-axis represents the total image quality, and L1, L2, L3, L4 and L5 are 352 × 288 (100%), 320 × 256 (80%), and 288 × 240, respectively. (70%), 272 × 224 (60%), and 176 × 144 (25%).

Referring to FIG. 10, when the bit rate is about 60 or more, the total image quality of the lines L1 to L4 is excellent, but when the bit rate is about 60 kbps or less, the total image quality of the line L5 having the lowest spatial resolution is rather excellent. .

Therefore, when transmitting an image, a frame of 100% size is compared with the case of transmitting to a receiver side while maintaining a frame size of 100% (in this case, a normal bit rate adjustment process using a quantization coefficient will be involved). When the size is reduced to have a spatial resolution of 176 × 144 (25%) and then transmitted to the receiving end, the quality of the image shown on the receiving end can be further improved. In addition, since the decoding time is reduced as the bit rate is lower, the power consumption at the receiving end can also be halved.

11 and 12 below, the original frame size (352 × 288) is transmitted as it is without being reduced (100% → 100%), and the one frame size (352 × 288 (100%)) is 176 × 144 (25). %) The state of the screen displayed on the receiver side when the transmission is reduced in size is shown.

When the original frame size (352 × 288) is transmitted without changing (100% → 100%), when the original frame size (352 × 288) is reduced to 176 × 144 (25%) size and transmitted In comparison, the PSNR of the image displayed on the receiver side is better (the PSNR of FIG. 12 is better).

However, when the original frame size (352 × 288) is reduced to 176 × 144 (25%) size and transmitted, the original frame size (352 × 288) is transmitted as it is without changing (100% → 100%). It is shown that the quality of the image displayed on the receiver side is better than that (). This may be because the decoding time and the resizing time are considered in addition to the PSNR according to the bit rate change.

The PSNR is a peak signal with respect to the noise ratio, and may be a criterion for indicating the degree of image quality, but the PSNR cannot be treated the same as the image quality. Accordingly, although the PSNR of FIG. 12 is better, the image quality confirmed through the naked eye of the receiver is substantially better than that of FIG. 11, so that the original frame size (352 × 288) is 176 × 144 (25%). The reduced transmission is advantageous in terms of image quality and power loss.

In particular, video between handheld devices is transmitted / received through a low transmission path having a low frequency band. Therefore, the amount of data in the image is reduced and transmitted. However, the lower the data bit rate, the lower the image quality.

 However, as described above, it has been found that the image quality is better when the spatial resolution is lower than the specific bit rate.

Accordingly, as in the present invention, in transmitting images between various image display apparatuses including a handheld device, total quality criteria in consideration of image quality and power consumption are set, and an optimal spatial resolution is calculated according to the total quality criteria. In the environment where the bandwidth is less than the specified value, the original video frame size is reduced to a predetermined size and transmitted. On the receiving end, the reduced and transmitted video frame is restored and displayed to the original frame size, so that the image quality at the receiving end is displayed. This can improve the power consumption by reducing the decoding time. Substantially, when the bandwidth is lower than a certain value, it is assumed that the other conditions are the same, and the image quality can be improved by about 1 db or more when transmitting by reducing the spatial resolution compared to the case of transmitting by adjusting the quantization coefficient. Power consumption has also been shown to be halved.

1 is a block diagram of a system for controlling a spatial resolution of an image according to the present invention.

2 shows an image transmission control method according to the present invention.

3 is a graph showing a relationship between a bit rate and video quality.

4 is a graph illustrating a change in decoding time for a single frame having various spatial resolutions.

5 is a graph illustrating a change in resizing time according to various spatial resolutions.

6 is a graph showing the relationship between bit rate and overall decoding time.

7 and 8 are graphs showing the relationship between the bit rate and the image quality for various spatial resolutions as the experimental results for the Stefan sequence and the mobile sequence, respectively.

9 and 10 are graphs illustrating changes in total image quality for various bit rates, respectively, as a result of experiments on the Stefan sequence and the Foreman sequence.

Fig. 11 shows the screen state displayed on the receiver side when the original frame size (352x288) is transmitted as it is without being reduced (100% → 100%).

Fig. 12 shows the screen state displayed on the receiver side when the original frame size 352 × 288 (100%) is reduced to 176 × 144 (25%) size and transmitted.

Claims (9)

delete delete delete delete In the video transmission control method, Monitoring network status to transmit video; Detecting a bandwidth available for the image transmission; According to the total quality standard considering the image quality and the power consumption, the optimal spatial resolution is selected to improve the image quality at the receiving end to receive the image and reduce the power consumption, and then select the selected optimal spatial resolution. Adjusting the frame size of the video so as to have it transmitted to a receiving end; Receiving the reduced image from the receiving end, and resizing the image to its original size and displaying the same; In the step of adjusting and transmitting the frame size of the image to the receiving end, the optimal spatial resolution is required to decode the video frame, the peak signal (PSNR) for the noise ratio, the relationship between the bit rate and distortion (distortion) of the image A method for controlling video transmission, characterized in that the selection is made according to a total quality measurement standard extracted by considering all the time and time required to resize a reduced image to its original size. The method of claim 5, wherein the relationship between the bit rate and distortion (distortion) of the video,

(D is the distortion measured in mean-square error (MSE), R is the bit rate of the decoded bit stream, and ε _x ² is the change in the input signal.) or,

(γ is a correlation coefficient of the data, ε _x ² is a scaling (scaling) parameter whose source distribution is determined according to Gaussian, Laplacian or uniform distribution). The method of claim 5, wherein the peak signal (PSNR) for the noise ratio,

or,

(R is the bit rate, q1, q2, q3 are constants that can be empirically inferred by experiment or observation, depending on the particular coding method and video content) Image transmission control method characterized in that defined by. The method of claim 5, wherein the time required to decode the video frame is:

(N _MB is the number of macroblocks, T _MB is the average time for macroblock decoding), or,

(O _MB is the time for selective enhancements such as variable-length DCT coefficient decoding, inverse quantization, and inverse DCT, a is a constant), or,

(N _MB = (Sx × Sy) / 16 × 16, b is a constant), or, T = t ₁ R + t ₂ S, or, T = t ₁ R + t ₂ S + t ₃ , (t ₃ is the display time) Image transmission control method characterized in that defined by. The method of claim 5, wherein the total quality measurement standard for the image is:

(φ is total quality measurement standard, Q is image quality, E is energy required to achieve image quality), or,

(w is the user's interest in energy consumption), or,

or, φ = f (R, S, w), Image transmission control method characterized in that defined by.

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