KR100203628B1 - Improved image coding system having functions for controlling generated amount of coded bit stream - Google Patents

Abstract

In the coding system including MC-DCT and quantization, the present invention calculates the complexity of an image to be currently encoded based on the spatial complexity of the previous frame reconstructed for motion estimation and compensation, and according to the result of the calculation, The present invention relates to a video encoding system having a bit generation amount adjusting function for adaptively adjusting a bit generation amount after encoding by selectively removing high frequency components of an input video signal using a dimensional discrete cosine transform. A spatial complexity value is calculated for each reconstructed previous frame for motion estimation and compensation, and the average spatial complexity value for the plurality of preset previous frames is calculated by averaging the spatial complexity values of the respective previous frames. Calculation means; The calculated average spatial complexity value of the plurality of frames is referred to as the complexity of the frame to be currently encoded by encoding means having DCT, quantization, and entropy encoding, and adaptively limits the frequency passband of the current frame input for encoding. Control means for generating a bandwidth determination signal corresponding to the calculated average spatial complexity value among a plurality of preset bandwidth determination signals; Discrete cosine transform means for converting an image signal in a spatial domain with respect to an input current frame signal into two-dimensional DCT transform coefficients in a frequency domain in units of M × N blocks by using a cosine function; Quantization means for quantizing two-dimensional DCT transform coefficient blocks in M × N units using a quantization parameter value to a finite number of values; Frequency selecting means for limiting a high pass band for the quantized DCT transform coefficient blocks to the determined bandwidth based on the generated bandwidth determining signal; And performing inverse quantization and inverse discrete cosine transform on each of the bandwidth-limited quantized DCT blocks to recover the original signal before encoding, and restore the bandwidth-limited frame signal restored to the original signal for motion estimation and compensation. By including the image reconstruction means provided to the encoding means, it is possible to effectively adjust the amount of bits generated after encoding without excessively increasing the step size during quantization in the encoding means.

Description

Image Coding System with Bit Rate Control

1 is a block diagram of a video encoding system having a bit generation amount adjusting function according to a preferred embodiment of the present invention.

2 is a detailed block diagram of the frequency selection block of FIG.

3 is a view showing a crystal region for high frequency component limitation determined according to the complexity of an 8x8 pixel block as an example according to the present invention;

* Explanation of symbols for main parts of the drawings

100, 170: frame memory 110: subtractor

120: image coding block 130: entropy coding block

140: transmission buffer 150: video decoding block

160: adder 180: current frame prediction block

210: space complexity calculation block 220: control block

230: frequency selection block 2310: DCT block

2320 quantization block 2330: frequency selector

2340 inverse quantization block 2350 IDCT block

The present invention relates to a video encoding system for compressing and encoding a video signal. More particularly, the present invention relates to a video encoding system for compressing and encoding a video signal, and more specifically, to compress and encode a video signal using motion compensation differential pulse code modulation (MC-DPCM). The present invention relates to an image encoding system having a bit generation amount adjustment function suitable for adaptively adjusting an amount of generated bits after encoding with reference to a variation of an input image signal predicted based on a spatial complexity of a previous frame.

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 in the case of high quality television (aka HDTV). 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 techniques for compressing data, hybrid coding techniques combining probabilistic coding and temporal and spatial compression are known to be the most efficient, and these techniques have been proposed by the World Standards Organization for example. It is widely disclosed in the recommendations of MPEG-1 and MPEG-2.

Most hybrid coding techniques use motion compensated DPCM (Differential Pulse Code Modulation) two-dimensional Discrete Cosine Transform (DCT), 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 method is described, for example, by Staffan Ericsson in Fixed and Adaptive Predictors for Hybrid Predictive / TransforM × Noding, IEEE Transactions on coM × Nnication, COM × N3, NO.12 (December 1985, December), or by NinoM × N and Ohtsuka. AM × Nion CoM × Nnsated InterfraM × NCoding ScheM × Nfor Television Pictures, IEEE Transactions on CoM × Nnication, COM × N0, NO. 1 (1982, January).

In general, two-dimensional DCT converts digital image data blocks, such as 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 CoM × Nnication, COM × N2, 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 pixel-based motion estimation method using a block matching algorithm, and the other is a pixel-based motion estimation method using a pixel cycling algorithm.

In the motion estimation method for estimating the displacement of an object as described above, the displacement is obtained for each pixel by using the pixel-based motion estimation method. This method has the advantage of being able to estimate pixel values more accurately and easily handle scale changes (e.g., zooming (zooM × Ng), a motion perpendicular to the image plane), while the motion vectors are each It is impossible to transmit substantially all of 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 extent to which the block has moved between frames) for the entire block is estimated for the current frame to be transmitted. Here, for 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, encoding techniques such as motion compensation DPCM, two-dimensional DCT, DCT coefficient quantization, and VLC (or entropy encoding) is transmitted to the output buffer of the image encoding system. When the next transmission point is stored at the transmitter, it is sent to the transmitter for transmission to the remote receiver. At this time, the transmission time point here is related to the size (ie, capacity) and transmission rate of the transmission buffer, and is controlled so that a malfunction (data overflow or data underflow) does not occur in the transmission buffer.

More specifically, various factors (e.g., image complexity) may cause a different amount of bits to be generated for each frame at the time of encoding. In view of this, in an image encoding system, the average bit rate may be kept constant. Control of the output buffer. 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 performed when encoding and transmitting the video data corresponding to each frame at the same data rate. In the case where the image to be encoded is complex (a large amount of high frequency components are generated), a large amount of bits is generated, resulting in a large quantization step, resulting in serious image quality degradation in the reproduced image. The high frequency component generated here is a component that is substantially insensitive to human visual characteristics (a component that hardly affects the image quality of a reproduced video).

Accordingly, the present invention is to solve the above-described problems of the prior art, in the coding system including MC-DCT, quantization, to be currently encoded based on the spatial complexity of the previous frame reconstructed for motion estimation and compensation An image having a bit generation amount adjustment function that can adaptively adjust the bit generation amount after encoding by calculating the complexity of the image and selectively removing high frequency components of the input video signal by using two-dimensional discrete cosine transform according to the calculation result. The purpose is to provide an encoding system.

In order to achieve the above object, the present invention provides a discrete cosine transform, quantization, and an error signal between an input current frame and a prediction frame obtained through motion estimation and compensation in units of macroblocks using the current frame and the reconstructed previous frame. A coded bit stream is encoded and encoded through an encoding means including entropy encoding, and the encoded bit stream is generated, and the quantization has a bit generation amount adjusting function of adjusting a step size based on the full state information of the bit stream stored in an output buffer. In the image encoding system, a spatial complexity value is calculated for each of the previous frames reconstructed for the motion estimation and compensation, and the spatial complexity values of the respective previous frames are averaged, respectively, for a plurality of preset previous frames. Calculate the mean spatial complexity value Between the complexity calculation means; And refer to the calculated average spatial complexity values of the plurality of frames as the complexity of the frame to be currently encoded by the encoding means, and predetermined to adaptively limit the frequency passband bandwidth of the current frame input for encoding. Control means for generating a bandwidth determination signal corresponding to the calculated average spatial complexity value among a plurality of bandwidth determination signals; Discrete cosine transform means for converting an image signal in a spatial domain with respect to the input current frame signal into a two-dimensional DCT transform coefficients in a frequency domain in units of M × N blocks using a cosine function; 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; Frequency selecting means for determining a high frequency pass band for the quantized DCT transform coefficient blocks based on the generated bandwidth determination signal, and limiting a high frequency pass band of each quantized DCT block to the determined bandwidth; And performing inverse quantization and inverse discrete cosine transform on each of the bandwidth-limited quantized DCT blocks to restore the original signal before encoding, and restore the bandwidth-limited frame signal restored to the original signal for the motion estimation and compensation. It provides a video encoding system having a bit generation amount adjustment function, characterized in that it further comprises a video restoring means provided to the encoding means as a current frame signal.

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.

1 is a block diagram of a video encoding system having a bit generation amount adjusting function according to a preferred 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 subtractor 110, an image encoding block 120, an entropy encoding block 130, a transmission buffer 140, and an image encoding. Block 150, adder 160, second frame memory 170, current frame prediction block 180, spatial complexity calculation block 210, control block 220, and frequency selection block 230.

Referring to FIG. 1, the input current frame signal is input to the next frequency selection block 230 stored in the first frame memory 100, and the frequency selection block 230 is provided from a control block 220 to be described later. Adaptively limiting the frequency of the input frame signal according to a control signal (bandwidth determining signal for frequency domain classification) calculated based on the complexity of the image according to the spatial complexity value of the previous frame reconstructed and reconstructed for encoding, that is, 2 The high frequency component (which is insensitive to the comparative human vision) of the input image is removed by using the dimensional discrete cosine transform (DCT). For the detailed operation of the frequency selection block 230, see FIG. Will be described later in detail. Then, the current frame signal in which the high frequency component is adaptively removed is provided to the subtractor 110 and the current frame prediction block 180 through line L11, respectively.

First, the subtractor 110 performs motion compensated predicted motion on the moving object provided from the current frame prediction block 180 described later through the line L19 from the current frame signal provided from the first frame memory 100 through the line L11. Subtract the current frame signal, and as a result, the data, i.e., the error signal representing the differential pixel value, is obtained by using discrete cosine transform (DCT) and one of the quantization methods well known in the art through the image coding block 120. It is then encoded into a series of quantized DCT transform coefficients. At this time, the quantization of the error signal in the image encoding block 120 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 140 described later through the line L21. Is adjusted.

Meanwhile, although the detailed illustration of FIG. 1 is omitted, the frequency selection block 230 is based on the bandwidth determination signal based on the calculated spatial complexity value information of the previous frame provided from the control block 220 described later according to the present invention. Two-dimensional DCT is used to remove (ie, filter) high frequency components that are relatively insensitive to human visual characteristics. Accordingly, the present invention can appropriately adjust the quantization step size in the quantization step in the image encoding block 120 that causes deterioration of image quality in the reproduced video even in a complex image accompanied by an increase in the encoded bit generation amount. A detailed process of adaptively restricting the passband of the input frame by using the bandwidth determination signal set based on the spatial complexity value information of the previous frame thus calculated will be described in detail later.

Next, the quantized DCT transform coefficients on line L13 are sent to entropy coding block 130 and image decoding block 150, respectively. In this case, the quantized DCT transform coefficients provided to the entropy coding block 130 are transmitted to a transmitter, not shown, for example, for transmission to a receiver by using a variable length coding technique.

Meanwhile, the line L13 provided from the image coding block 120 to the image decoding block 150.

The quantized DCT transform coefficients of the image are transformed back into a reconstructed frame signal through inverse quantization and inverse discrete cosine transform, and then provided to the adder 160, which is reconstructed from the image decoding block 150. The reconstructed previous frame signal is generated by adding the frame signal and the predicted current frame signal provided from the current frame prediction block 180 to be described later through the line L19, and the reconstructed previous frame signal is the second frame memory 170. Are stored in. Accordingly, the immediately previous frame signal for every frame encoded through this path is continuously updated, and the reconstructed previous frame signal thus updated is provided to the current frame prediction block 180 described later for motion estimation and compensation. .

In addition, the reconstructed reconstructed previous frame signal stored in the second frame memory 170 is provided to the spatial complexity calculation block 210 described below through line L16 for calculating the spatial complexity of the input frame according to the present invention.

On the other hand, in the current frame prediction block 180, the current frame signal on the line L11 provided from the first frame memory 100 described above and the reconstructed previous frame on the line L15 provided from the second frame memory 170 described above. A predetermined block (eg, 8 × 8 or 16 × 16 DCT) in a predetermined search range (eg, 16 * 16 or 32 * 32 search range) of the previous frame reconstructed using a block matching algorithm based on the signal. After predicting the current frame in units of blocks), the predicted current frame signal is generated on the line L19 and provided to the subtractor 110 and the adder 160, respectively. In this case, the switch SW on the line L19 is turned on / off according to the control signal CS from the system controller (not shown), and when the switch SW is on, the current encoding mode is an inter mode. On the contrary, when off, this means that the current encoding mode is an intra mode. Accordingly, the subtractor 110 provides an error signal between the current frame signal and the predicted frame signal to the image encoding block 120 during inter-mode encoding, and transmits the current frame signal itself to the image encoding block 120 during intra-mode encoding. to provide.

Further, a set of motion vectors for the current frame prediction block (8x8 or 16x16 block) selected on the line L17 is generated and provided to the entropy coding block 130 described above. Here, the sets of detected motion vectors are predicted in a block (8x8 or 16x16 block) of the current frame and a preset search area (eg, 16x16 or 32x32 search range) in the previous frame. Thus, in the above-described entropy coding block 130, the quantized DCT transform coefficients on the line L13 together with the sets of motion vectors on the line L17 are encoded by using, for example, a variable length coding technique. Generates an encoded bit stream.

Meanwhile, the spatial complexity calculation block 210 calculates the spatial complexity of the image of the restored previous frame provided from the second frame memory 170 through the line L16, that is, by using the dispersion value (standard deviation) of the image signal. The spatial complexity related to the information amount of the video signal to be encoded is calculated, and the spatial complexity of the previous frame thus calculated is referred to as the image complexity of the frame to be currently encoded, and in the present invention, based on the calculated spatial complexity of the previous frame. In the quantization step of the image encoding block 120, a high frequency component relatively insensitive to a human visual characteristic is adaptively (or selectively) removed (that is, filtered).

In the present invention, the variance value (standard deviation) of the video signal is used when calculating the spatial complexity of the reconstructed previous frame. In the case of the variance value used here, if the value is large, the result of performing the DCT is a high frequency component. The distribution of transform coefficients is inadequate for compressing the data because it will contain many (components with relatively insensitive human visual characteristics). A good image for ideal data compression is the case where there is no high frequency component but only DC component, and the distribution of transformed coefficients has only one value at the position of (0, 0). In addition, when the variance value is large, motion compensation may not be performed properly, and as a result, the structure of the motion compensated image is not suitable for encoding. Therefore, such spatial complexity can be interpreted as the amount of information of the video signal, that is, the amount of data to be encoded and transmitted.

For example, assuming that one frame has a size of M * M, Ip is a picture of a previous frame reconstructed and reconstructed after encoding, and Ic is a picture of a current frame input for encoding. The pixel value of the Ip image at the x, y) position is Ip (x, y). At this time, the complexity of the currently input Ic image is calculated for the image signal of the previous frame reconstructed after coding (DCT, quantization) for motion estimation and compensation. ACT) can be used.

In the above formula (1), MIp means an average value for the reconstructed previous frame Ip image, and the average value MIp for this Ip image is calculated as follows (2).

As described above, the reason for using the ACT value of the previous frame reconstructed as the complexity of the frame to be currently encoded is that the characteristics of the video signal do not change rapidly every frame.

Therefore, it can be said that the calculated spatial complexity ACT value is related to the information amount (bit generation amount) of the image. If the current encoded image is complex, the calculated spatial complexity ACT value will be relatively large, and vice versa. The resulting spatial complexity ACT value will be small.

In view of this aspect, the spatial complexity ACT value between the restored previous frames calculated at the time of encoding may be interpreted as a value related to the amount of information to be transmitted. In the calculation of the spatial complexity ACT value of the reconstructed previous frame according to the present invention, since the reconstructed previous frame signal required in the process of performing the motion estimation and compensation by the encoding system is stored in the frame memory, such encoding is performed. Using part of the system, one can easily obtain the spatial complexity ACT value of the desired restored previous frame. Then, the complexity ACT value calculated in the spatial complexity calculation block 210 is provided to the next weight generation block 220 as described above.

On the other hand, the control block 220 generates a frequency bandwidth determination signal B on the line L23 to limit the frequency of the input image based on the spatial complexity ACT value provided from the spatial complexity calculation block 210. 230). Here, the bandwidth determination signal B for the area discrimination generated here and provided to the frequency selection block 230 limits the frequency band of the input frame signal. In this case, the bandwidth determination signal B necessary for classifying the frequency domain is calculated by the following method, and the process of setting the frequency domain of the input image to be restricted according to the present invention using the bandwidth determination signal B is described in the appended second. It will be described later in detail with reference to the drawings.

More specifically, the process of outputting the region division value B by using the spatial complexity ACT value output from the spatial complexity calculation block 210 in the control block 220 is expressed by Equation (3) below.

The process of obtaining MACT and SACT in Equation (3) is as follows. That is, when the frame rate of the video signal is 30, the average of 30 ACT values calculated for 1 second is MACT, and the standard deviation of these values is SACT. Therefore, the area discriminating value B can be obtained by comparing the MACT and SACT values thus obtained with the ACT values generated in each frame. That is, the control block 220 determines the area division value B using the average and standard deviation of the ACT values generated during the previous 30 frames. As a result, the current generated ACT values obtained through this process are again 30 It is used to find the mean value and standard deviation of the frame. Accordingly, the control block 220 discards the first obtained ACT value (the oldest ACT value in time) among the ACT values of the 30 frames generated previously, and averages the newly obtained ACT value from the motion error calculation block 210. To find the standard deviation. Of course, the currently generated ACT value is not used to calculate the mean and standard deviation after the 31st frame.

As apparent from the above Equation (3), the area discriminating value B has an integer value between 1 and 4, which is an error signal (the current frame on the line L11 and the prediction frame on the line L19) output from the subtractor 110 described above. This is to adaptively adjust the bandwidth according to the ACT value in the two-dimensional low pass filtering before quantization of the DCT transform coefficients of the discrete cosine transform of the difference signal).

On the other hand, the frequency selection block 230 limits the high frequency components which are relatively insensitive to time in the input image based on the bandwidth determination signal B for frequency domain division provided from the control block 220 described above. Substantially, it can be divided into two-dimensional frequency conversion process and frequency selection fixation. In this case, the two-dimensional frequency conversion process uses a two-dimensional DFT, and in the frequency selection process based on the bandwidth determination signal B provided from the control block 220 described above. The pass band of the 2D-converted video signal is determined.

Next, in the frequency selection block 230 as described above, the input image is two-dimensional DFT transformed, and the frequency of the two-dimensional DFT-converted image signal is selected based on the bandwidth determination signal B for frequency domain classification. This will be described in detail with reference to FIG. 2.

First, the frequency selection block 230 performs two-dimensional DCT transformation on an input image. As is well known in the art, the DCT transformation process is well known to reflect the spatial similarity of an image signal. The technique is widely applied in the process of encoding a video signal. Therefore, detailed description is omitted here. Therefore, the present invention uses DCT transform having such characteristics (reflecting spatial similarity) as an effective frequency selection technique according to the complexity of the video signal. The frequency selection process according to the present invention returns to the frequency domain reflecting the characteristics of the image signal better than the simple frequency converter method, and as a result, it is possible to increase the efficiency when selecting a frequency for the input image. That is, the same number of DCT transform coefficients has more information about the video signal than the Discrete Fourier Transform (DFT) transform coefficients.

FIG. 2 shows a detailed block diagram of the frequency selection block 230 according to the present invention shown in FIG. As shown in the figure, the frequency selection block 230 of the present invention includes a dct block 2310, a quantization block 2320, a frequency selector 2330, an inverse quantization block 2340, and an IDCT block 2350. do.

In FIG. 2, the DCT block 2310 utilizes the similarity of the spatial domain of the video signal. N * using the cosine function for the video signal (pixel data) of the spatial domain based on Equation (4) below. 2D DCT transform coefficients in a frequency domain of N units, for example, 8 × 8N = 8, are provided to the next quantization block 2320.

In Equation (4), F (u, v) means the converted DCT coefficient, and f (x, y) means the input video signal. Here, x and y mean frequencies in the horizontal and vertical directions of the pixel data. Next, the quantization block 2320 quantizes the DCT coefficients which have been two-dimensionally transformed by the above Equation (4) to a finite number of values through, for example, nonlinear operations. In this case, a QP value is used in the quantization process of the DCT transform coefficient, and an operation that takes an integer value by performing F (u, v) / (2 × QP) on the transformed DCT coefficient is an example of a representative quantization process. have.

On the other hand, the frequency selector 2320 is based on the bandwidth determination signal B for frequency domain division provided from the control block 220 of FIG. To determine its frequency. As described above, since the bandwidth determination signal B for frequency domain division is an integer value between 1 and 4, the frequency selected according to this is as follows.

That is, the frequency selector 2330 selects a specific frequency from the converted frequency F (k, l). Here, k and l are integer values between 0 and N-1. Therefore, the value output from the frequency selector 2330 becomes a signal from which a specific frequency component (ie, a high frequency component) is removed. For example, if N = 8, its pass frequency will be determined as shown in FIG.

As shown in FIG. 3, when the bandwidth predetermined signal B for frequency domain division provided from the control block 220 of FIG. 1 to the frequency selector 2330 of FIG. 2 through the line L23 is 1, the conversion frequency F ( k, l) are all selected, and when the B value is 2, 3, or 4, as shown in FIG. That is, when the value of B in FIG. 3 is 4, frequencies below the dotted line such as F (1, 7), F (2, 6), etc. are mapped to mode 0. FIG.

Next, as described above, the quantized DCT transform coefficients of which the frequency (high frequency component) of the specific region is removed according to the bandwidth determination signal B value determined based on the complexity of the previous image encoded are dequantized block 2340 of the next stage. And an original signal (pixel data) through the IDCT block 2350. At this time, the inverse transformation process of the inverse quantized DCT transformation coefficient in the IDCT block 2350 is as shown in Equation (5) below.

In Equation (5), f (x, y) means inversely transformed video signal (pixel data), and F (u, v) means transformed DCT coefficient. Here, u and v denote horizontal and vertical frequencies in the converted DCT coefficients, and x and y denote horizontal and vertical positions of the pixel data.

As a result, the IDCT block 2350 is based on the image signal from which the frequency of a specific region is removed according to the image complexity using the subtractor 110 and the current frame prediction block 180 of FIG. According to the bandwidth determination signal B is calculated to provide a video signal in which the high frequency component of the image is selectively (or adaptive) removed (an image signal in which a high frequency component of a specific region is replaced with a zero value).

Accordingly, in the image encoding block 120 of FIG. 1, in the case of a complex image, encoding (quantization) is performed in a state in which a high frequency component of an image relatively insensitive to human vision is selectively (or adaptively) removed as described above. Therefore, the low frequency signal, which is a visually important component, can be encoded (quantized) while generating less quantization error. If the low pass bandwidth of the frequency is not limited as in the present invention despite the complicated image, as a result, the amount of bits generated after encoding increases and the quantization step size becomes large. A large number of quantization errors are generated, and as a result, image quality deterioration due to quantization will be caused in the playback image of the receiver.

As described above, according to the present invention, the complexity of the input image to be currently encoded is calculated by using spatial complexity information calculated for each frame by using a previous frame reconstructed and reconstructed after encoding for motion estimation and compensation during encoding. If the current input image is a complex image according to the result of the calculation, by applying a weight corresponding thereto, the high frequency component of the image insensitive to the human vision is firstly removed, and then the MC-DCT, quantization, etc. are encoded. The amount of bits generated after encoding can be effectively adjusted without excessive step size increase in the quantization step. Therefore, according to the present invention, when reconstructing and displaying an encoded image, it is possible to effectively reduce image quality deterioration due to quantization error inevitably present in the reproduced image.

Claims (5)

Compression means including discrete cosine transform, quantization, and entropy encoding for the error signal between the input current frame and the prediction frame obtained through motion estimation and compensation in units of macroblocks using the current frame and the reconstructed previous frame. A video encoding system having a bit generation amount adjustment function of encoding and generating a coded bit stream, wherein the quantization is adjusted based on the full state information of the bit stream stored in an output buffer. A spatial complexity calculation is performed to calculate a spatial complexity value for each of the previous frames reconstructed for compensation, and to calculate an average spatial complexity value for a plurality of preset previous frames by averaging the spatial complexity values of the respective previous frames. Way ; A predetermined average spatial complexity value of the plurality of frames is referred to as the complexity of the frame to be currently encoded by the encoding means, and a preset value for adaptively limiting the frequency passband bandwidth of the current frame input for encoding Control means for generating a bandwidth determination signal corresponding to the calculated average spatial complexity value among a plurality of bandwidth determination signals; Discrete cosine transform means for converting an image signal in a spatial domain with respect to the input current frame signal into two-dimensional DCT transform coefficients in a frequency domain in units of M × N blocks using a cosine function; 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; Frequency selecting means for determining a high frequency pass band for the quantized DCT transform coefficient blocks based on the generated bandwidth determination signal, and limiting a high frequency pass band of each quantized DCT transform coefficient block to the determined bandwidth; Inverse quantization and inverse discrete cosine transform are performed on each of the bandwidth-limited quantized DCT blocks to restore the original signal before encoding, and restore the bandwidth-limited frame signal restored to the original signal for the motion estimation and compensation. And a picture restoring means provided to said encoding means as a frame signal. The average bandwidth of the plurality of frames transmitted per second and the average error of each of the predetermined bandwidth determination signal is obtained by averaging the calculated spatial complexity of each frame, the spatial complexity of each frame. Image encoding system having a bit generation amount adjustment function, which is determined using a standard deviation of a value. 3. The bit of claim 1, wherein the plurality of predetermined bandwidth determination signals comprise four bandwidth determination signals of integer values for setting different filter coefficients of the respective DCT transform coefficient blocks. Image coding system with generation amount control function. The method of claim 1, wherein the discrete cosine converting means has a bit generation amount adjusting function, characterized in that for converting the video signal of the spatial domain for the current frame signal to the two-dimensional DCT transform coefficients of 8 × 8 block units. Video encoding system. The method of claim 1 or 4, wherein the frequency selecting means maps a high frequency component below the generated bandwidth determination signal to zero values for each of the quantized DCT transform coefficient blocks. An image encoding system having a bit generation amount adjustment function.