KR100229791B1 - Adaptive image coding system having functions for controlling bandpath of video signals - Google Patents

Abstract

According to the present invention, a scene change of an input image is detected based on short-time statistics of a plurality of frames for a predetermined time period based on the average pixel value of the corresponding frame to be encoded and the average value of each frame, The present invention relates to an adaptive video encoding system having a band limit function for efficiently controlling the amount of bits generated after encoding by adaptively removing a high frequency component of an input video signal by using a band limiting technique through filtering during scene changeover. To this end, the present invention is to extract the average value of the pixel for each frame sequentially input for encoding; Using the extracted average values, a prediction value for the corresponding frame is extracted, and a prediction error value between the average (MIp) value and the extracted prediction value is calculated for each input frame, and the prediction calculated for each frame Calculating short-time statistics for a predetermined time by calculating an average and a standard deviation of the error values; Limiting the passband of the current input frame using a filtering technique based on a comparison result between the statistical characteristics of the current input frame and the calculated short-time characteristics; A scene change situation having a large complexity in the input image by including technical means for selectively providing a band-limited frame from which a high frequency component has been removed through the current input frame itself or a filtering technique to an encoding means having a DCT, quantization, or VLC technique. Even if this occurs, the amount of bits generated after encoding can be effectively adjusted without excessive step size increase during quantization in the encoding means.

Description

Adaptive Video Coding System with Band Limit Function

1 is a block diagram of an adaptive video encoding system having a band limit function according to a preferred embodiment of the present invention.

2 is a detailed block diagram of the preprocessing block of FIG.

3 is a view showing a determination region for high frequency component limitation determined as one fixed level for an 8x8 pixel block as an example when the input image is a scene change portion according to the present invention;

4 is a view showing a decision region for limiting high frequency components that is adaptively determined based on the complexity of an 8x8 pixel block as an example when the input image is a scene change portion according to the present invention.

5 is an exemplary diagram for an 8x8 pixel block as an example in accordance with the present invention.

6 is an exemplary view showing a one-dimensional low pass filter coefficient of order 7 as an example according to the present invention.

7 is an exemplary diagram illustrating a horizontal filtering process at (0,4) and a vertical filtering process at (3,0) as an example according to another exemplary embodiment of the present invention.

8 is an exemplary view showing a 2D lowpass filter coefficient of 3x3 order as an example according to another embodiment of the present invention.

9 is an exemplary diagram illustrating a two-dimensional filtering process at a position.

10 is a detailed block diagram of a frame prediction block shown in FIG. 2 according to another embodiment of the present invention.

<Description of the code | symbol about the principal part of drawing>

100, 180: frame memory 110: preprocessing block

115: switching block 120: subtractor

130: image coding block 140: entropy coding block

150: transmission buffer 160: video decoding block

170: adder 190: current frame prediction block

1110: statistical characteristic calculation block 1120: control block

1130: memory block 1140: band limit block

1141: DCT block 1143: quantization block

1145 frequency selector 1147 dequantization block

1149: IDCT block

The present invention relates to a video encoding system for compression encoding video signals. More particularly, the present invention relates to a video encoding system that detects a scene change of an input video using an average value of a plurality of frame signals during a predetermined time input for compression encoding. The present invention relates to an adaptive video encoding system having a band limit function suitable for adaptively adjusting the amount of generated bits after encoding in accordance with a detection result.

As is well known in the art, the transmission of discrete video signals can maintain better image quality than analog signals. When a video signal consisting of a series of image "frames" is represented in digital form, a significant amount of data must be transmitted, especially for high quality televisions (aka HDTVs). However, since the usable frequency range of the conventional transmission channel is limited, in order to transmit a large amount of digital data, it is necessary to compress the transmitted data and reduce the amount thereof. Among the various compression methods for compressing data, hybrid coding which combines probabilistic coding with temporal and spatial compression is known to be the most efficient, and these techniques have been proposed by the World Standards Organization for example. It is widely disclosed in recommendations such as MPEG-1 and MPEG2.

Most hybrid coding techniques use motion compensated DCPM (differential pulse code modulation), two-dimensional DCT (discrete cosine transform), quantization of DCT coefficients, VLC (variable length coding), and the like. The motion compensation DPCM determines a motion of an object between a current frame and a previous frame, and predicts a current frame according to the motion of the object to generate a difference signal representing a difference between the current frame and a predicted value. This can be done for example in Staffan Ericsson's "Fixed and Adaptive Predictors for Hybrid Predictive / Transform Coding", IEEE Transactions on Communication, COM33, NO.12 (December 1985, December), or "A motion Compensated Interframe" by Ninomiy and Ohtsuka. Coding Scheme for Television Pictures ", IEEE Transactions on Communication, COM30, NO.1 (January, 1982).

In general, two-dimensional DCT converts digital image data blocks, for example, 8x8 blocks, into DCT conversion coefficients by using or removing spatial redundancy between image data. This technique is described in Chen and Pratt's "Scene Adaptive Coder", IEEE Transactions on Communication, COM # 32, NO.3 (March, 1984). The DCT conversion coefficient may be processed through a quantizer, zigzag scan, VLC, etc. to effectively reduce (or compress) the amount of data to be transmitted.

More specifically, the motion compensation DPCM predicts the current frame from the previous frame according to the motion of the object estimated between the current frame and the previous frame. The estimated motion may be represented by a two-dimensional motion vector representing the displacement between the previous frame and the current frame.

Typically, there are several approaches to estimating the displacement of an object. These are generally classified into two types, one of which is a block-by-block motion estimation method using a block matching algorithm and the other is a pixel-by-pixel motion estimation method using a pixel circulation algorithm.

In the motion estimation method for estimating the displacement of an object as described above, the displacement is obtained for all of the pixels using the pixel-based motion estimation method. This method has the advantage that the pixel value can be estimated more accurately and the scale change (e.g., zooming, which is a movement perpendicular to the image plane) can be easily different, while the motion vector is different for each pixel. Since it is determined, it is impossible to transmit substantially all the motion vectors to the receiver as large amounts of motion vectors occur.

In addition, in block-by-block motion estimation, a block having a predetermined size of the current frame is moved by one pixel in a search range of a previous frame and compared with the corresponding blocks to determine an optimal matching block having a minimum error value. From this, the interframe displacement vector (the degree of block movement between frames) for the entire block is estimated for the current frame to be transmitted. Here, in determining the similarity between two corresponding blocks between the current frame and the previous frame, the average absolute difference, the mean square difference, etc. are mainly used, as is well known in the art.

On the other hand, the image bit stream encoded by the encoding technique as described above, that is, the encoding scheme such as motion compensation DPCM, two-dimensional DCT, DCT coefficient quantization and VLC (or entropy encoding) is transmitted to the output side of the image encoding system. The next transmission point stored in the buffer is sent to the transmitter for transmission to the remote destination. The transmission time here is related to the size (i.e. capacity) and transfer rate of the transmission buffer and is controlled so that no malfunction (data overflow or data underflow) in the transmission buffer occurs.

More specifically, the amount of bits generated for each frame at the time of encoding is changed due to various factors (for example, scene change of the input image). In view of this, in the video encoding system, the average bit rate is kept constant. The control of the output side transmission buffer is performed. That is, the video encoding system checks the bit generation amount up to the frame currently encoded based on the data fullness state information of the output transmission buffer and adjusts the bit amount to be allocated in the current frame. In other words, in the conventional typical video encoding system, the amount of bits generated in the encoding system is adjusted by controlling the quantization step size (QP) substantially based on the data full state information of the output transmission buffer, that is, if the amount of bits generated before has been large, The bit generation amount is controlled by reducing the bit generation amount by adjusting the step size largely, and in the opposite case, by adjusting the quantization step size small to increase the bit generation amount.

However, as described above, the conventional method of adjusting the bit generation amount by adjusting the quantization step size based on the data fullness state information of the output side transmission buffer is to transmit the video data corresponding to each frame at the same data rate. In the case where the input image to be encoded is a scene change image, that is, an image having low correlation between frames on the time axis, the efficiency is lowered in the encoding process such as motion compensation, thereby increasing the amount of bits generated. As a result, there is a problem that serious image quality deterioration is caused in the reproduced image.

Accordingly, the present invention is to solve the above-described problems of the prior art, and based on the short-time statistics of a plurality of frames for a predetermined time based on the average of the pixel value of the corresponding frame to be encoded and the average value of each frame. By detecting the scene change and adaptively removing the high frequency components of the input video signal by limiting the pass band during the scene change of the image according to the detection result, a band limit function that can efficiently adjust the amount of bits generated after encoding is provided. It is an object of the present invention to provide an adaptive image encoding system.

In order to achieve the above object, the present invention provides an intra encoding mode for performing discrete cosine change, quantization, and entropy encoding on an input current frame, and motion estimation using the current frame, the current frame, and a reconstructed previous frame. And an encoding unit having an inter encoding mode for performing discrete cosine change, quantization, and entropy encoding on a difference signal between predicted frames obtained through compensation, comprising: for each frame sequentially input for encoding; A statistical characteristic calculation block for extracting an average Mp value of pixels representing the statistical characteristic; A memory block that sequentially stores an average Mp value for each extracted frame for a predetermined time period; Extracting a predicted value for a corresponding frame input by using the average (MIp) values for a plurality of frames corresponding to the stored predetermined time, and between the average (MIp) value and the extracted predicted value for each input frame A prediction error value is calculated, and the average and standard deviation of the prediction error values calculated for each frame are calculated to calculate short-time statistics for the predetermined time, and is more temporal than the frames used for calculating the short-time statistics. A control block for generating a filtering control signal of the current input frame input for encoding based on a comparison result between the statistical characteristics of the current input frame and the calculated short-time statistics; A band limiting block generating a band limited frame by removing a high frequency component by applying a filtering technique to the current input frame input for encoding based on a filter coefficient determined according to the generated filtering control signal; And the encoding means converting the current input frame itself or the band limited frame, which is switched according to a switching control signal generated based on a comparison result between the short-time statistics provided from the control block and the statistical characteristics of the current input frame. It provides an adaptive video encoding system having a band limiting function further comprising a switching means for providing.

The above and other objects and various advantages of the present invention will become more apparent from the preferred embodiments of the present invention described below with reference to the accompanying drawings by those skilled in the art.

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

As described above, in the hybrid encoding system employing encoding techniques such as motion compensation DPCM, two-dimensional DCT, quantization of DCT coefficients, and VLC (or entropy encoding) for efficient encoding of video signals, the input video is adjacent to each other. In the case of a scene transition image having a low correlation on the time axis between frames, the quantization step size becomes excessively large due to a large amount of bits, which may cause deterioration of image quality (deterioration of image quality due to quantization error) in the present invention. In consideration of this, if it is determined whether the input video is a scene change part and first determines that the scene is a scene change part, the band of the input image can be adaptively adjusted using a filtering technique for a predetermined time (ie, during a scene change). By restricting and removing high frequency components that are relatively insensitive to human visual characteristics Used to suppress an increase in the amount of bits generated to have the greatest technical feature, it is possible to obtain a more natural reproduced image by minimizing the quantization error in encoding through such technical means.

1 is a block diagram of an adaptive video encoding system having a band limit function according to an embodiment of the present invention. As shown in the figure, the image encoding system of the present invention includes a first frame memory 100, a preprocessing block 110, a switching block 115, a subtractor 120, an image encoding block 130, an entropy encoding block. 140, a transmission buffer 150, an image decoding block 160, an adder 170, a second frame memory 180, and a current frame prediction block 190.

Referring to FIG. 1, an input current frame signal is stored in the first frame memory 100 on the input side. The current frame signal stored in the first frame memory 100 is a switching block (described later through line L11). And connected to one side input b of 115, and also through line L12 to preprocessing block 110, described in detail later with reference to FIG. Here, the other input c of the switching block 115 is connected to one side output (frame signal output) of the preprocessing block 110 via the line L14, and the switching of the switching block 115 is performed through the line L13. By control signal CS based on the statistical characteristic calculation of the input frame signal provided from 110. The specific switching operation of such a switching block 115 will be described later in detail.

Meanwhile, the preprocessing block 110 constitutes the most characteristic constituent member in the present invention. The statistical characteristics, through the analysis and investigation of the frame signal provided from the first frame memory 100 through the line L12 according to the present invention, In other words, the average value of each input frame signal is calculated, and a predetermined time (for example, 1 second) for a plurality of frames (for example, 30 frames) for which the average MIp (average of pixel values) is calculated for each frame. Determining whether the input video signal is a scene change part based on short-term statistics calculated based on the statistical characteristic information. By restricting the pass band of each frame signal, adaptively removes high frequency components that are relatively insensitive to human visual characteristics, and then enters the switching block 115 through the line L15. Provided as force c. Detailed operation of the preprocessing block 110 will be described later in detail with reference to the accompanying drawings.

On the other hand, the switching block 115 connects the input frame signal on the line L11 or the band limited frame signal on the line L15 on the line L16 based on the switching control signal CS from the preprocessing block 110, and the frame signal on the line L16. (The input frame signal itself or the band limited frame signal) is provided to the subtractor 120 or the image coding block 130 via the switch SW, and also to the current frame prediction block 190. Here, the switch SW switches the contact points according to control from a system controller (not shown), for example, a microprocessor. In the intra mode encoding, the fixed contact point on the line L16 is connected to the variable contact point on the line L17. In inter-mode encoding, the fixed contact on the line L16 is connected to the input of the subtractor 120. Accordingly, the image encoding block 130 described later uses DCT, quantization, or the like to encode the current frame signal itself (an input frame signal or a frame signal limited through the preprocessing block 110) on the line L17 during intra mode encoding. In the inter-mode encoding, the error signal on the line L18 (the difference between the current frame signal on the line L16 and the predicted frame signal on the line L22) will be encoded using a technique such as DCT or quantization. In other words, in the intra mode encoding, the input frame signal itself is encoded (DCT, quantization, entropy encoding, etc.) without using motion estimation and compensation techniques. Since the encoding here is substantially the same as that of the inter mode encoding. In the following description, it is assumed that inter-mode encoding is an example for the purpose of understanding and convenience of explanation.

First, in the subtractor 120 from the current frame prediction block 190 described later through the line L21 from the current frame signal from which the high frequency component provided through the line L16 and the switch SW is not removed or the high frequency component is selectively removed. The motion compensated predicted current frame signal is subtracted with respect to the provided moving object, and as a result, the data, i.e., the error signal representing the differential pixel value, is transmitted through the image coding block 130 in the discrete cosine transform (DCT) and the technical field. By using any of the well-known quantization methods, it is encoded into a series of quantized DCT transform coefficients. At this time, the quantization of the error signal in the image encoding block 130 is based on the step size based on the quantization parameter QP determined according to the data fullness state information provided from the output side transmission buffer 150 described later through the line L23. Is adjusted.

Next, the quantized DCT transform coefficients on line L19 are sent to entropy coding block 140 and image decoding block 160, respectively. Here, the quantized DCT transform coefficients provided to the entropy coding block 140 are encoded by, for example, a variable length coding scheme, and provided to the transmission buffer 150 at the output side. It is delivered to the transmitter not shown for transmission.

On the other hand, the quantized DCT transform coefficients on the line L19 provided from the image coding block 130 to the image decoding block 160 are converted into a frame signal reconstructed again through inverse quantization and inverse discrete cosine transform, and then added to the next stage. And a reconstructed frame signal from the image decoding block 160 and a predicted current frame signal provided from the current frame prediction block 190 to be described later through the line L21. Generated previous frame signal, and the reconstructed previous frame signal is stored in the second frame memory 180. Therefore, the immediately previous frame signal for every frame encoded through this path is continuously updated, and the reconstructed previous frame signal thus updated is sent to the current frame prediction block 190 described below for motion estimation and compensation. Is provided.

On the other hand, in the current frame prediction block 190, the current frame signal on the line L16 in which the high frequency component is not removed or the current frame signal in which the high frequency component on the line L16 provided from the preprocessing block 110 according to the present invention is selectively removed. And a preset search range (eg, 32 × 32 or 16 × 16) of the previous frame reconstructed using the block matching algorithm based on the reconstructed previous frame signal on the line L20 provided from the second frame memory 180 described above. In the search range, the motion is estimated by a predetermined block (for example, 16 × 16 or 8 × 8 DCT blocks), the current frame is predicted, and the predicted current frame signal is generated on the line L21 and the subtractor ( 120 and an adder 170, respectively.

The current frame prediction block 190 also generates a set of motion vectors for each selected block (16x16 or 8x8 blocks) on line L22 and provides it to the entropy coding block 140 described above. Here, the sets of motion vectors detected are predicted in the block of the current frame (16x16 or 8x8 block) and the preset search area (e.g., 32x32 or 16x16 search range) in the previous frame. It is the displacement between the most similar candidate blocks. Accordingly, in the entropy coding block 140 described above, the quantized DCT transform coefficients on the line L19 together with the sets of the motion vectors on the line L22 generate an encoded bit stream by, for example, a variable length coding technique. .

Next, it is the most characteristic part of the present invention, and it is determined whether the input image is a scene change part, and when the input image is a scene change part, the high frequency component of the input image is selectively selected through band limitation using a filtering technique or the like. The operation process in the preprocessing block 110 for providing the band-limited video signal as an input frame signal on the line L16 will be described in detail.

FIG. 2 shows a detailed block diagram of the preprocessing block shown in FIG. As shown in the figure, the preprocessing block 110 of the present invention includes a statistical characteristic calculation block 1110, a control block 1120, a memory block 1130, and a band limiting block 1140.

Referring to FIG. 2, the statistical characteristic calculation block 1110 receives an input image on the line L12 and calculates a parameter for determining whether the current image is an image for scene change. The average value MIp of the video signal is used. That is, as an example, when the current input image is Ip, the pixel value of the Ip image at the position of (x, y) is Ip (x, y).

Therefore, the average value MIp of each input frame signal is obtained as shown in Equation 1 below.

[Equation 1]

In the above Equation 1, M and N are integer values, respectively, indicating the horizontal and vertical directions of the video signal. Then, the parameters thus extracted, that is, the average value MIp of each frame, are provided to the next control block 1120.

The reason for using the average value MIp extracted as described above as the statistical characteristic information to be used for determining whether the scene transition part is the scene change part is that if the input video signal is not the scene change part, (Average) is not significantly different from the previous video signal. On the contrary, if the input video signal is a scene change part, the statistical characteristics of the extracted video signal appear much different from the statistical characteristics of the previous video signal. Therefore, in the present invention, it is determined whether or not to change the scene for the input image by using the temporal change of the statistical characteristic value, this determination will be performed in the control block 1120 described later.

That is, the control block 1120 determines whether the current input image is a scene change part using the parameters provided from the statistical characteristic calculation block 1110, that is, the average (MIp) value of each frame. The decision signal is provided to the next pass low pass filtering block 1140 via line L14. That is, in the scene change part of the video signal, there is not much similarity between the previous video and the current video due to the change in time. As a result, the encoding efficiency is low during the processing of the coding system such as motion compensation. By generating a bit of, a large quantization error in the quantization step (which causes a deterioration in image quality due to a blocking phenomenon in the reconstructed reproduced video on the receiver side) is accompanied. Accordingly, the present invention detects the scene change of the input image in order to reduce such a phenomenon occurring during the scene change of the image.

More specifically, in the control block 1120, the statistical characteristics (short-term statistics) for a predetermined time (for example, one second) and the corresponding frame input from the statistical characteristic calculation block 1110 are used to detect the scene change of the input image. The parameter (average) value is compared to determine whether the scene is changed. The procedure for obtaining such short-time statistics is as follows.

First, there are various methods for obtaining a statistical characteristic for a predetermined time with respect to an input image. However, in the present invention, a parameter that is currently input from a statistical characteristic for a predetermined time previously calculated using a one-dimensional prediction device is used. Predict the value for Then, an error between the predicted value and the statistical characteristic value of the input frame is calculated, and it is determined whether or not the current input image is scene change production based on the predicted error calculated therein. For this calculation, the control block 1120 stores the MIp value input every frame in the statistical characteristic calculation block 1110 in the memory block 1130. Here, the one-dimensional prediction process is as follows.

For example, assuming that the variable input at time n1 is x (n1) and the output variable is y (n1), the feedback value y (n1) and the immediately input value are fed back by feeding back the previously output value. The predicted value y (n) and the predicted error value e (n) of x (n) input at time n from (x (n1)) are respectively calculated by the following equation.

[Formula 2]

(In the above formula, p value is a constant value between 0 and 1, and absolute is an operation that takes an absolute value. Y (n) and x (n) values are based on the current point of time n. After calculating the output signal of the control block 1120 to calculate the frame, the y (n) value is stored in the memory block 1130 as y (n-1), and the x (n) value is x (n−). 1) If the value is stored in the memory block 1130 and x (n) of the next frame is input, the above equation is calculated using these values.)

That is, the y (n) value is the value predicted by the x (n) value, which is calculated from the y (n-1) value previously output and the x (n) value previously input. In operation 1120, when an x (n) value currently input is input, e (n), that is, a prediction error is calculated from a value of y (n) (that is, a value predicted from a past generated value). From this calculated value, it is determined whether the input video is a scene change part.

On the other hand, in the above [Formula 2], the p value can be set according to the cycle or the minimum occurrence interval of the scene transition occurs, in the present invention, as an example, it is assumed that the time for 1 second. That is, it is assumed that the scene of the video signal can be continuously generated every 1 second. If the value (p) is set too small, the result is assuming that the video signal continues to occur at short time intervals, which is not consistent with the characteristics of the actual video signal. Similarly, it does not match the characteristics of the actual video signal. If this time is t, only t seconds of video data is used to calculate the statistics of the video signal. In other words, when [p] in Equation 2 is large (i.e., close to 1), the value multiplied by y (n-1) becomes smaller, resulting in using only statistics for a short time. Given a small value (ie, a value close to zero), the characteristics of the current frame are predicted using the characteristics of the image signal for a long time. Therefore, when the frame rate of the video signal is FR (frame / sec), the time of one frame corresponds to 1 / FR. Therefore, if the time for t seconds is determined, p value can be obtained, and this process is calculated by the following equation.

[Equation 3]

(Here, threshold is the criterion for negligible values.)

As an example, the threshold value is 0.01, the q value is 0.666667, and the q value is calculated as 1-0.215 = 0.785 as a maximum value multiplying the statistics of video signals before t seconds so as to be ignored. Therefore, the control block 1120 calculates the y (n) value using the q value set as described above. At this time, the process of obtaining q value is closely related to the threshold value. This value is multiplied by the image signal characteristic at 31 frames because if the characteristic is used for 1 second, only the characteristic for 30 frames is used. You will understand.

Next, a process of extracting the output value of the control block 1120 using the prediction error e (n) calculated through the above process is as follows.

First, the control block 1120 calculates the prediction error mean Me and the standard deviation Se for a predetermined time by using the prediction error values calculated for each frame as described above. The mean Me and the standard deviation Se are calculated. The process of calculating is as follows.

As described above, the statistics of the video signal are the average value of the input video signal, that is, MIp. Using this value, assuming that x (n) of Equation 2 described above, the value of each prediction error value eMIp can be calculated. have. In this case, the application process may be regarded as the average value MIp instead of the input value x (n), and the prediction value may be calculated through each calculation process, and the error value eMIp may be calculated. Then, you can calculate the Me and Se values by using the resulting values to find the mean and standard deviation over one second. That is, when the frame rate of the video signal is 30, 30 average and standard deviation values for the prediction error for 1 second are generated, respectively, and the average and standard deviation of these values are obtained.

Meanwhile, since the prediction error value calculated as described above occurs every frame, when one new prediction error value is calculated, the prediction error value calculated in the past 31st frame is discarded and replaced with the newly calculated prediction error value to the next calculation. I use it. Therefore, for this calculation, the memory block 1130 should store eMIp, which is values of prediction errors calculated by using the MIp value input every frame in the control block 1120, for 1 second.

Therefore, if the value of the prediction error currently calculated in the control block 1120 is eMIp (0), the output signal B in the control block 1120 uses the three statistical values eMIp, Me, Se calculated as described above. It is calculated as follows.

[Equation 4]

Therefore, the output signal B calculated as described above and generated on the line L14 is provided to the band limiting block 1140. When the output signal B on the line L14 is 0, MIp (the characteristic of the video signal currently input) The value of 0) means that it is not a scene change part because there is not much change compared with the previous short time characteristic. On the other hand, when the output signal B on the line L14 is 1, the characteristic of the currently input video signal is the previous short time. Compared to the characteristic, it means that it is a scene change part because there are many changes. That is, the control block 1120 detects whether or not the average of the pixel value of the current input frame suddenly changes by using the short-time statistics obtained from the frame for the previous predetermined time based on the statistical characteristics of each frame, and based on the detection result It is determined whether the current input video is a scene change video.

As a result, the band limiting block 1140 performs appropriate band limiting processing, that is, filtering on the current frame signal on the line L12 provided from the first frame memory 100 of FIG. 1 based on the output signal B on the line L14. A frame signal from which a predetermined high frequency component is removed is generated on a line L15. When filtering the input frame signal on the line L12, in the band limiting block 1140, as shown in Fig. 3 as an example, all values below Z (1,7) and Z (2,6) are zero (0). ), The bandwidth is limited and filtered. The output frame signal from which the high frequency component has been removed is then connected to the line L16 via the c­a condensation of the switching block 115 of FIG.

On the other hand, in the control block 1120, when the band limiting block 1140 described below according to the present invention is configured to filter the input frame signal to generate a frame signal from which high frequency components have been removed, The output signal B may be calculated as shown in the following equation so that the input frame may be filtered adaptively (or selectively) in consideration of the complexity of the input image without filtering the input frame.

[Equation 5]

Therefore, the output signal B calculated as described above and generated on the line L14 is provided to the band limiting block 1140. When the output signal B on the line L14 is 1, MIp (the characteristic of the video signal currently input) The value of 0) means that it is not a scene change part because there is not much change compared with the previous short time characteristic, and when the output signal B on the line L14 is 2, 3, 4, the characteristic of the currently input video signal Compared with the previous short-time characteristic, it means that it is a scene change part because there is much change. That is, the control block 1120 detects whether or not the average of the pixel value of the current input frame is suddenly changed by using the short time statistics obtained from the frame for the previous predetermined time based on the statistical characteristics of each frame, and based on the detection result. It is determined whether the current input video is a scene change video.

As a result, in the band limiting block 1140, on the basis of the output signal B on the line L14, a corresponding band limiting process corresponding to the current frame signal on the line L12 provided from the first frame memory 100 of FIG. In other words, adaptive filtering is performed. That is, when filtering the input frame signal on the line L12, the band limiting block 1140 corresponds to the output signal B from the control block 1120 based on the complexity of the input image, as shown in FIG. 4 as an example. By mapping the value below the output value (that is, the value below the dotted line in FIG. 4) to a zero value, the bandwidth is limited and filtered. In other words, according to this embodiment, the high frequency component removal level of the input frame signal is selectively (or adaptively) adjusted according to the complexity of the input frame.

Then, the output frame signal from which the high frequency component is adaptively (or selectively) removed as described above is connected on the line L16 via the c \ a path of the switching block 114 of FIG. Accordingly, in the image code and the block 130 of FIG. 1, the frame signal on the line L17 in which the high frequency component relatively insensitive to the human visual characteristics is selectively or adaptively removed is encoded using DCT, quantization, or the like. will be.

In addition, the control block 1120 sequentially updates the prediction error eMIp values for each frame stored in the memory block 1130 according to the sequential input of the current frame, that is, when the eMIp (0) for one new frame is inputted. The stored value of eMIp (30) is replaced by the value of eMIp (29), the value of eMIp (29) is replaced by the value of eMIp (28), and finally the value of eMIp (1) is converted to the value of eMIp (0). By replacing, it is possible to calculate a newly updated short time statistic for one input image, and this updating process is performed every frame. As a result, the time for which the parameter for each frame extracted from the statistical characteristic calculation block 1110 is stored in the memory block 1130 corresponds to 30 frames, and after 30 frames, the parameter is not used to calculate short-time statistics. As such, the memory block 1130 that stores the parameters of each frame for short-term statistical calculation may be simply configured using, for example, a first-in, first-out buffer.

Meanwhile, in the control block 1120, the short-time statistics of the previous input image and the statistical characteristics of the current input image for a predetermined time (for example, 1 second) calculated using 30 frames of eMIp stored in the memory block 1130. When it is determined whether the current input image is a scene change part based on the parameter MIp, the control signal CS (eg, high or high) for switching the contact point in the switching block 115 of FIG. A logic signal having a low level) is generated on the line L13.

In other words, in the control block 1120, when it is determined that the current input image is not the scene change part as a result of comparing the short-time statistics for a predetermined time with respect to the previous image and the statistical characteristic (MIp) of the current input image, the line L13. A logic signal of high or low level is generated on the control block so that ba of the switching block 115 shown in FIG. 1 is connected. Alternatively, when it is determined that the current input image is a scene change part, it is low on line L13. Alternatively, a high level logic signal is generated to control ca of the switching block 115 shown in FIG. 1 to be connected. As a result, based on the control signal CS on the line L13 provided from the control block 1120, if the switching block 115 ba is connected, the current input frame signal itself on the line L11 is the line L16 for adaptive intra / inter mode encoding. On the contrary, when ca of the switching block 115 is connected, the frame signal on the line L15 provided by the band limiting block 1140 or the frame signal from which the high frequency component is removed is connected on the line L16.

On the other hand, when the band limiting block 1140 is configured to generate a frame signal from which high frequency components have been removed through filtering, on the line L15 as an input frame signal, the method for removing the high frequency components is one-dimensional. Low pass filtering, 2D low pass filtering, band limiting using Discrete Fourier Transform (DET), and band limiting using Discrete Cosine Transform (DCT). Techniques, etc.

As described above, when providing a frame from which a high frequency component relatively insensitive to human visual characteristics is removed as an input frame signal as described above, one-dimensional low pass filtering technique, which is one of techniques for removing the high frequency component, This is performed by multiplying the low pass filter by the input video signal. That is, when the value of each pixel for an image of one block of N × M (for example, 8 × 8 block) is f (x, y), one block is 8 as shown in FIG. 5 as an example. In the case of a block of x8, the position values x and y of the pixel in the horizontal and vertical directions have integer values between 0 and 7, and each value has a level value between 0 and 255. That is, as can be seen from Fig. 5, the position values in the horizontal and vertical directions of each pixel of the 8x8 block have a value of f (0,0) to f (7,7).

On the other hand, as the one-dimensional low pass filter in the present invention, as shown in Fig. 6 as an example, it is assumed that the one-dimensional low pass filter coefficient has seven orders. The low pass filter is an example of a low pass filter that band-limits the signal to have a frequency bandwidth of fs / 4 because the frequency bandwidth is fs / 2 when the sampling frequency of the input video signal is fs.

Therefore, in the band limiting block 1140, the process of performing one-dimensional low pass filtering on the image signal according to the present invention performs one-dimensional low pass filtering on each direction since the input image signal is a two-dimensional signal in the horizontal and vertical directions. This can be achieved by This process is illustrated in detail in FIG. 7 which shows a horizontal filtering process at (0,4) and a vertical filtering process at (3,0). That is, if the low pass filtered signal in the vertical direction at the position of (x, y) is z (x, y), this is calculated by the following equation.

[Equation 6]

In the above Equation 6, T means the order of the filter, so T = 7. Thus, u and v values have integer values between -3 and 3. In the above Equation 6, the k (u) value is a filter coefficient value, and the f (x, y) value is a pixel value. If the (yu) value of f (x, yu) in Equation 5 is smaller than 0, it is set to 0, or when it is larger than the M-1 value corresponding to the image size of one frame, M-1 Value. This is a method of setting the end value when the pixel value exists only in the area, that is, 0 to M-1, and this filtering method is a technique known in the art.

Therefore, if the filtering is performed at all pixel positions as shown in [Equation 6], as shown in FIG. 7 as an example, one-dimensional filtering in the horizontal and vertical directions can be obtained. In this case, in the process of performing such filtering at all pixel positions, horizontal filtering may be performed first, and then vertical filtering may be performed again or the order of the horizontal filtering may be changed again. .

On the other hand, the one-dimensional low-pass filtering as described above may be configured to completely remove or partially remove the high frequency components of the input video signal by using only one preset filter coefficient (or fixed), but the complexity of the input video In consideration of this, the complexity may be configured to adaptively (or selectively) remove high frequency components of the input image using a plurality of filter coefficients (for example, four). In this case, when the input frame is adaptively filtered using a plurality of filter coefficients, the hardware implementation may be more complicated than the image filtering using one preset filter coefficient, but the image encoding block 130 of FIG. Another advantage is that in the quantization process, precise control of the quantization step size is possible. Therefore, in the case of adaptive filtering using a plurality of filter coefficients as described above, it may be selectively applied according to its application range.

On the other hand, two-dimensional low pass filtering among the techniques for the high frequency component removal of the input frame, as shown in Fig. 5, is performed for each block of an image of one block of NxM (e.g., 8x8 blocks). Assume that the value of the pixel is f (x, y), and as an example, as shown in Fig. 8, the two-dimensional low pass filter coefficient has a 9th order having 3 orders. Similarly, it depends on the filter coefficient k. The value of k (0,0) is 1/2, and the other values have a value of 1/16.

Accordingly, the process of performing the two-dimensional low pass filtering of the input frame signal on the line L12 in the band limiting block 1140 according to the present invention, for example, shows a process of performing filtering at the position of f (3,3). As shown in. In Fig. 9, the sum of the product between the filter coefficient and the overlapping pixels gives a filtered result. If the two-dimensional low pass filtered signal at the position of (x, y) is called Z (x, y), this value is calculated by the following equation.

[Formula 7]

In the above formula, T means the order of the filter, so T = 3. Thus, the u value has an integer value between -1 and 1. In the above equation, k (u, v) is a filter coefficient value, and f (x, y) is a pixel value. At this time, the same as in the above-described one-dimensional low-pass filtering, if the (xu), (yv) value of f (xu, yv) is less than 0 in the above formula is set to 0, or corresponds to the image size of one frame If the value becomes larger than the M-1 value, the M-1 value is used. Therefore, if the filtering is performed at the positions of all the pixels as in the above formula, as shown in FIG. 9, for example, two-dimensional filtering in the horizontal and vertical directions can be obtained.

On the other hand, when the band limiting technique using the DFT is adopted among the techniques for removing the high frequency components of the input frame, the band limiting block 1140 determines the bandwidth for frequency domain division provided to the control block 1120 described above. On the basis of the output signal B to limit the high frequency components which are relatively insensitive to the time in the input image, the process can be substantially divided into two-dimensional frequency conversion process and frequency selection process. In the frequency selection process, a passband of the DFT-converted video signal is determined based on the output signal B provided from the control block 1120.

Next, in the band limiting block 1140, the input frame on the line L12 is two-dimensional DFT transformed and the frequency of the two-dimensional DFT-converted video signal is selected based on the output signal B for bandwidth determination in detail. Explain.

First, the band limiting block 1140 uses the similarity of the spatial domain of the input image signal. The band-limited block 1140 uses the Fourier function to convert the image signal (pixel data) of the spatial domain using a Fourier function, for example, according to the following equation. For example, two-dimensional DFT transform coefficients of a frequency domain of 8x8 units are converted.

Equation 8

In the above formula, f (u, v) denotes the value of each pixel, u denotes the position in the horizontal direction, and v denotes the position of the pixel in the vertical direction. Therefore, the value for each pixel of the N × M block has the following value. That is, when N = 8 u and v have a value between 0 and 7. At this time, each value has an integer value between 0 and 255. In addition, in the above formula, Z (k, l) means a converted signal, and k, l means frequency components in the horizontal and vertical directions, respectively. Therefore, when N = 8, an 8x8 DFT block, that is, a signal in the spatial domain is converted into a signal in the frequency domain.

More specifically, in the band limiting block 1140, the DFT conversion coefficients obtained through the above-described process are passed based on the output signal B for bandwidth determination provided from the control block 1120 through the line L14. Determine the frequency band to be At this time, as shown in Equation 5, the output signal B for bandwidth determination may be set to an integer value between 1 and 4, and the selected frequency is as follows.

That is, the band limiting block 1140 selects a specific frequency from the converted frequency Z (k, l). Here, k, l is an integer value between 0 and N-1. Accordingly, the value output from the band limit block 1140 becomes a signal from which a specific frequency component (ie, a high frequency component) is removed. For example, in the case of N = 8, as shown in FIG. 4 as an example, the pass frequency band will be determined.

Accordingly, as shown in FIG. 4, the frequency below the dotted line corresponding to each of the frequencies according to the output signal B for determining the bandwidth provided from the control block 1120 to the band limiting block 1140 via the line L14 is all zero. Do not choose. That is, when the B value is 4 in FIG. 4, all frequencies below the dotted line such as Z (1,7), Z (2,6), etc. are mapped to 0. Alternatively, a single predetermined filter coefficient may be used to limit high frequency components of a predetermined level or higher (replace high frequency components of a fixed level or more with 0, etc.) in response to the output signal B from the control block 1120. In this case, the implementation will be somewhat easier compared to the adaptive (or optional) band limitation.

Next, as described above, the DFT transform coefficients (signals in the frequency domain) from which the frequency (high frequency component) of the specific region is removed according to the output signal B value for determining the bandwidth determined based on the complexity of the image are expressed as follows. The inverse is transformed into the original spatial signal.

[Equation 9]

In the above formula, f (u, v) denotes the value of each pixel, u and v denote the position of the pixel in the horizontal and vertical directions, Z (k, l) denotes the converted signal, and k denotes frequency components in the horizontal and vertical directions, respectively. Therefore, when N = 8, 8x8 DFT blocks in the frequency domain are converted into a signal (pixel data) in the spatial domain.

As a result, in the band limiting block 1140, when the input image is the scene change portion on the line L15, the image signal is selectively calculated based on the complexity of the input image, that is, the frequency of the specific region is selectively removed according to the complexity of the image. According to the output signal B for bandwidth determination, a frame signal in which the high frequency component of the image is selectively (or adaptively) removed is generated (a zeroing signal in which a high frequency component of a specific region is replaced with a zero value). A frame signal in which high frequency components which are relatively inferior to human visual characteristics are selectively removed) are provided to the subtractor 120 and the current frame prediction block 190 via ca and line L16 of the switching block 115 of FIG. (Inter mode encoding) or provided to the image encoding block 130 via ca and line L17 of the switching block 115 (intra mode encoding).

On the other hand, when the band limiting technique using DCT is employed among the techniques for removing high frequency components of the input frame, the band limiting block 1140 determines the bandwidth for frequency domain division provided to the control block 1120 described above. On the basis of the output signal B to limit the high frequency components which are relatively insensitive to the time in the input image, the process can be divided into two-dimensional frequency conversion process and frequency selection process. In this case, discrete cosine is used in the two-dimensional frequency conversion process. By using the conversion (DCT), in the frequency selection process, the pass band of the DCT-converted video signal is determined based on the output signal B provided from the control block 1120.

Next, a process of selecting a frequency of the 2D DCT transformed image signal based on the output signal B for determining the bandwidth for frequency domain division and inputting the 2D DCT transformed image in the band limiting block 1140. It will be described in detail with reference to the accompanying Figure 10.

First, the band limiting block 1140 performs 2D DCT conversion on the input image. As is well known in the art, the DCT conversion process is known to reflect the spatial similarity of the image signal. The converter method is widely applied in the process of encoding a video signal. Therefore, detailed description is omitted here. Therefore, in the present embodiment, when the input image is a scene change part, DCT transform having such characteristics (reflecting spatial similarity) is used as an effective frequency selection technique according to the complexity of the image signal. Such a frequency selection process in the present invention returns to the frequency domain by better reflecting the characteristics of the image signal than a simple frequency conversion technique, and as a result, it is possible to increase the efficiency when selecting a frequency for the input image.

FIG. 10 shows a detailed block diagram of the band limiting block 1140 according to the present invention shown in FIG. As shown in the figure, the band limiting block 1140 includes a DCT block 1141, a quantization block 1143, a frequency selector 1145, an inverse quantization block 1147, and an IDCT block 1149.

In Fig. 10, the DCT block 1141 uses the similarity of the spatial domain of the video signal, and according to the following expression, the video signal (pixel data) of the spatial domain is co-signed by MxN units, for example. For example, two-dimensional DCT transform coefficients of a frequency domain of 8x8 units are converted and provided to the next quantization block 1143.

Equation 10

In the above equation, F (u, v) means the transformed DCT coefficient, and f (x, y) means the input image signal. Here, x, y means the position in the horizontal and vertical direction of the pixel data, u, v means the frequency in the horizontal and vertical direction in the transformed DCT coefficients. The quantization block 1143 then quantizes the two-dimensional transformed DCT coefficients using the above-described equation, for example, using a nonlinear operation to a finite number of values. In this case, the QP value is used in the quantization process of the DCT transform coefficient. When the transformed DCT coefficient is F (u, v), an operation of performing an integer value by performing F (u, v) / (2 * QP) is performed. This is an example of a representative quantization process.

On the other hand, the frequency selector 1145 uses the output signal B for bandwidth determination provided from the control block 1120 of FIG. 2 through the line L14 for the DCT transform coefficients quantized through the above-described process. Determine the frequency passed. In this case, as shown in Equation 5, the output signal B for bandwidth determination may be set to an integer value between 1 and 4, and the selected frequency is as follows.

That is, the frequency selector 1145 selects a specific frequency from the converted frequency Z (k, l). Here, k, l is an integer value between 0 and N-1. Therefore, the value output from the frequency selector 1145 becomes a signal from which a specific frequency component (ie, a high frequency component) is removed. For example, when N = 8, its pass frequency will be determined as shown in FIG.

Therefore, as shown in FIG. 4, the frequency below the dotted line corresponding to each of the frequencies according to the output signal B for determining the bandwidth provided from the control block 1120 to the frequency selector 1145 through the line L14 is all zero. Do not choose. That is, in the case where the B value is 4 in FIG. 4, frequencies below the dotted line such as Z (1,7), Z (2,6), etc. are all mapped to 0. FIG. Alternatively, a single predetermined filter coefficient may be used to limit high frequency components of a predetermined level or higher (replace high frequency components of a fixed level or more with 0, etc.) in response to the output signal B from the control block 1120. In this case, the implementation will be somewhat easier compared to the adaptive (or optional) band limitation.

Next, as described above, when the input image is a scene change part, the quantized DCT from which the frequency (high frequency component) of the specific region is removed according to the output signal B value for bandwidth determination determined based on the complexity of the input image. The conversion coefficients are restored to the original signal (pixel data) through the next inverse quantization block 1147 and the IDCT block 1149. At this time, the inverse transformation process of the inverse quantized DCT transformation coefficient in the IDCT block 1149 is as shown in the following equation.

[Equation 11]

In the above equation, f (x, y) means inversely transformed video signal (pixel data), and F (u, v) means transformed DCT coefficient. Here, u, v means frequencies in the horizontal and vertical directions in the transformed DCT coefficients, and x, y means positions in the horizontal and vertical directions of the pixel data.

As a result, in the IDCT block 1149, when the input image is the scene change portion on the line L15, the bandwidth calculated based on the complexity of the input image, that is, the image signal from which the frequency of a specific region is selectively removed according to the complexity of the image. According to the output signal B for the determination, a frame signal in which the high frequency component of the image is selectively (or adaptively) removed (the image signal in which the high frequency component of the specific region is replaced with 0 value) is generated. Frame signals in which the high frequency components are relatively insensitive to the visual characteristics of?) Are provided to the subtractor 120 and the current frame prediction block 190 via ca and line L16 of the switching block 115 of FIG. Inter mode encoding) or provided to the image encoding block 130 via ca and line L17 of the switching block 115 (intra mode encoding).

As a result, in the image encoding block 130 of FIG. 1, when the input image is a complicated scene change part, as described above, the adaptive band limiting (band or limiting using one-dimensional or two-dimensional low pass filtering, DFT or DCT) Through encoding (quantization) is performed in the state in which the high frequency component of the image is relatively insensitive to human vision, it can be encoded while generating a low quantization error for the low frequency signal, which is a visually important component. If, despite the complex scene transition image, the band pass frequency is not adaptively limited (reduced high frequency components) as in the present invention, the amount of bits generated after encoding increases, resulting in a large quantization step size. A large number of quantization errors occur in the frequency band (high frequency to low frequency band), and as a result, image quality degradation due to quantization will be caused in the playback image on the receiving side.

As described above, according to the present invention, the short-term statistics of a plurality of frames for a predetermined time and the statistical characteristics of the currently input video frame are used for the input video input to the video encoding system for encoding the desired bit rate. It is determined whether the video inputted for current encoding is a complex scene change part. As a result of the determination, if the input image is a complex scene change part, an image signal insensitive to human visual characteristics is applied by applying an adaptive band limit using a filtering technique. By first removing the high-frequency components of the encoding and then performing encoding such as DCT and quantization in both inter and intra encoding, even if a scene transition situation with a large complexity occurs in the input image, encoding without increasing an excessive quantization step size in the quantization step The amount of bits generated after Typically it can be adjusted.

Therefore, according to the present invention, it is possible to effectively suppress deterioration in image quality due to quantization error inevitably present in the reproduced image when the encoded image is restored and displayed on the receiving side.

Claims (12)

Intra-coding mode for performing discrete cosine transform, quantization, and entropy encoding on an input current frame, and a differential signal between the current frame and a prediction frame obtained through motion estimation and compensation using the current frame and a reconstructed previous frame. An image encoding system comprising encoding means having an inter encoding mode for performing discrete cosine transform, quantization, and entropy encoding for a pixel, comprising: an average Mp of pixels representing a statistical property for each frame sequentially input for encoding A statistical characteristic calculation block for extracting a value; A memory block that sequentially stores an average MIp value for each of the extracted frames for a predetermined time period; Extracting a predicted value for a corresponding frame input by using the average (MIp) values for a plurality of frames corresponding to the stored predetermined time, and between the average (MIp) value and the extracted predicted value for each input frame A prediction error value is calculated, and the average and standard deviation of the prediction error values calculated for each frame are calculated to calculate short-time statistics for the predetermined time period, and the temporal time is higher than the frames used for calculating the short-time statistics. A control block for generating a filtering control signal of the current input frame input for encoding based on a comparison result between the statistical characteristics of the current input frame existing later and the calculated short-time statistics; A band limiting block generating a band limited frame by removing a high frequency component by applying a filtering technique to the current input frame input for encoding based on a filter coefficient determined according to the generated filtering control signal; And the encoding means converting the current input frame itself or the band limited frame, which is switched according to a switching control signal generated based on a comparison result between the short-time statistics provided from the control block and the statistical characteristics of the current input frame. An adaptive video encoding system having a band limiting function, further comprising a switching means for providing. The adaptive video encoding system of claim 1, wherein the plurality of frames for a predetermined time period is a previous 30 frames immediately adjacent in time to the frame input for the encoding. . The method of claim 1, wherein the band limiting block selectively removes a high frequency component level of the current input frame through one-dimensional low pass filtering using any one of a plurality of filter coefficients having different values. Adaptive Video Coding System with Band Limit Function. 4. The adaptive video encoding system of claim 3, wherein the one-dimensional low pass filtering is sequentially performed in a horizontal ­ vertical or vertical ­ horizontal direction of each pixel position in the 8x8 block. The adaptive video encoding system of claim 1, wherein the band limiting block removes high frequency components of the current input frame through two-dimensional low pass filtering. 6. The band limiting block of claim 5, wherein the band limiting block selectively removes a high frequency component level of the current input frame by using one of a plurality of filter coefficients having different values. Adaptive Video Coding System. The method of claim 1, wherein the band limiting block converts the video signal in the spatial domain for the current input frame into DFT transform coefficients in the frequency domain in M × N block units using a Discrete Fourier Transform. Determine a high frequency pass band for the converted DFT transform coefficient blocks based on a filtering control signal for band limitation, limit the high pass band of each converted DFT transform coefficient block to the determined bandwidth, And the band limited frame signal is generated by reconstructing the original signal through an inverse discrete Fourier transform for each of the limited DFT blocks. The method of claim 7, wherein the bandwidth limit of the current input frame is adaptively performed with any one of a plurality of levels preset according to the complexity of the input frame. Video encoding system. The bandwidth limiting function of claim 7 or 8, wherein the bandwidth limiting function maps a high frequency component below the determined bandwidth to a zero value for each of the transformed DFT transform coefficient blocks. Adaptive Image Coding System. The method of claim 1, wherein the band limiting block is: Discrete cosine for converting the video signal in the spatial domain for the current input frame signal into a two-dimensional DCT transform coefficients of the frequency domain in the unit of M × N block using a cosine function Conversion means; Quantization means for quantizing the two-dimensional DCT transform coefficient blocks in M × N units using a quantization parameter value to a finite number of values; A frequency for determining a high frequency pass band for the quantized DCT transform coefficient blocks based on the filtering control signal provided from the control block, and limiting a high frequency pass band of each of the quantized DCT transform coefficient blocks to the determined bandwidth Selection means; And performing inverse quantization and inverse discrete cosine transform on each of the bandwidth-limited quantized DCT blocks to reconstruct the original signal before encoding to generate a band-limited frame. And an image restoring means provided to said switching means as a signal. 12. The adaptation of claim 10, wherein the bandwidth limitation of the current input frame is adaptively performed at any one of a plurality of levels preset according to the complexity of the input frame. Video encoding system. The bandwidth limiting function of claim 10 or 11, wherein the bandwidth limiting function maps a high frequency component below the determined bandwidth to a zero value for each of the transformed DCT transform coefficient blocks. Adaptive Image Coding System.