JP4857243B2 - Image encoding apparatus, control method therefor, and computer program - Google Patents

Description

  The present invention relates to an image encoding device, a control method thereof, and a computer program.

  With the recent development of multimedia, various video compression encoding methods have been proposed. Typical examples are MPEG-1, 2, 4 and H.264. There is something like H.264. In these compression encoding processes, an original image (image) included in a moving image is divided into predetermined regions called blocks, and motion compensation prediction and DCT conversion processing are performed in units of the divided blocks. . In addition, when performing motion compensation prediction, an image obtained by local decoding of already encoded image data is used as a reference image, so that a decoding process is required even when encoding is performed.

  In addition, when compressing and encoding an image in accordance with the MPEG system, the amount of code often varies greatly depending on the spatial frequency characteristics, which are characteristics of the image itself, the scene, and the quantization scale value. An important technique for realizing a decoded image with good image quality in realizing an image coding apparatus having such coding characteristics is code amount control.

  TM5 (Test Model 5) is generally used as one of the code amount control algorithms. The code amount control algorithm according to TM5 is composed of the following three steps, and the code amount is controlled in the following three steps so that the bit rate is constant for each GOP (Group Of Picture).

(STEP1)
The target code amount of the picture to be encoded from now is determined. Rgop, which is a code amount that can be used in the current GOP, is calculated by the following equation (1).
Rgop = (ni + np + nb) * (bits_rate / picture_rate) (1)
Here, ni, np, and nb are the number of remaining pictures in the current GOP of I, P, and B pictures, bits_rate represents the target bit rate, and picture_rate represents the picture rate.

Further, the complexity of the picture is obtained from the encoding result for each of the I, P, and B pictures by the following equation (2).
Xi = Ri * Qi
Xp = Rp * Qp (2)
Xb = Rb * Qb
Here, Xi, Xp, and Xb are also called complexity. Ri, Rp, and Rb are code amounts obtained as a result of encoding I, P, and B pictures, respectively. Further, Qi, Qp and Qb are average values of Q scales in all macroblocks in the I, P and B pictures, respectively. From the equations (1) and (2), the target code amounts Ti, Tp, and Tb for each of the I, P, and B pictures can be obtained by the following equation (3).
Ti = max {(Rgop / (1+ ((Np * Xp) / (Xi * Kp)) + ((Nb * Xb) / (Xi * Kb))))), (bit_rat
e / (8 * picture_rate))}
Tp = max {(Rgop / (Np + (Nb * Kp * Xb) / (Kb * Xp))), (bit_rate / (8 * picture_rate))}
Tb = max {(Rgop / (Nb + (Np * Kb * Xp) / (Kp * Xb))), (bit_rate / (8 * picture_rate))}
... (3)
Np and Nb are the remaining number of P and B pictures in the current GOP, respectively, and constants Kp = 1.0 and Kb = 1.4.

(STEP2)
Three virtual buffers are used for each of the I, P, and B pictures, and the difference between the target code amount obtained by Expression (3) and the generated code amount is managed. The data accumulation amount of the virtual buffer is fed back, and the reference value of the Q scale is set for the macroblock to be encoded next so that the actual generated code amount approaches the target code amount based on the data accumulation amount. For example, when the current picture type is a P picture, the difference between the target code amount and the generated code amount can be obtained by arithmetic processing according to the following equation (4).
dp, j = dp, 0 + Bp, j−1 − ((Tp * (j−1)) / MB_cnt) (4)
Here, the subscript j is the number of the macroblock in the picture. dp, 0 represents the initial fullness of the virtual buffer, Bp, j represents the total code amount up to the j-th macroblock, and MB_cnt represents the number of macroblocks in the picture. Bp, j represents the total code amount up to the j-th macroblock, and MB_cnt represents the number of macroblocks in the picture.

Next, when the reference value of the Q scale in the j-th macroblock is obtained using dp, j (hereinafter referred to as “dj”), equation (5) is obtained.
Qj = (dj * 31) / r (5)
Where r = 2 * bits_rate / picture_rate (6)
It is.

(STEP3)
A process of finally determining the quantization scale is executed based on the spatial activity of the macroblock to be encoded so that the visual characteristics, that is, the image quality of the decoded image is improved.
ACTj = 1+ min (vblk1, vblk2, ..., vblk8) (7)
In the equation (7), vblk1 to vblk4 indicate spatial activities in 8 × 8 sub-blocks in the macroblock of the frame structure. Further, vblk5 to vblk8 indicate the 8 × 8 sub-block spatial activity in the field-structured macroblock. Here, the calculation of the space activity can be obtained by the following equations (8) and (9).
vblk = Σ (Pi−Pbar) ² (8)
Pbar = (1/64) * ΣPi (9)
Here, Pi is a pixel value in the i-th macroblock, and Σ in equations (8) and (9) is an operation of i = 1 to 64. Next, ACTj obtained by the equation (7) is normalized by the following equation (10).

N_ACTj = (2 * ACTj + AVG_ACT) / (ACTj + AVG_ACT) (10)
Here, AVG_ACT is a reference value of ACTj in a previously encoded picture, and finally a quantization scale (Q scale value) MQUANTj is obtained by the following equation (11).

MQUANTj = Qj * N_ACTj (11)
According to the above TM5 algorithm, a large amount of code is allocated to the I picture by the processing of STEP1, and the code amount is in a flat portion (low spatial activity) that is visually noticeable in the picture. A lot will be allocated.

  As an encoding method applying such a TM5 method, a method for determining a target code amount so that an SN ratio between an image signal and a locally decoded image is a certain value has been proposed (see Patent Document 1). . This proposed method has the effect of stabilizing the image quality for all pictures by setting a target code amount that keeps the SN ratio constant.

  As an improved method of the proposed method, a method of setting the code amount of each picture of I picture, P picture, and B picture to an optimum value has been proposed (see Patent Document 2). In this improved method, the code amount of each frame (I picture, P picture, B picture) is distributed and controlled so that the SN ratio of the I picture is larger than the SN ratio of the B picture. That is, by controlling the code amount of each frame (I picture, P picture, B picture) so that the coding error of the I picture is smaller than the coding error of the B picture, the image quality of the I picture that is the origin of the GOP There is an effect of improving.

Furthermore, an encoding method using inter-screen differences has also been proposed (see Patent Document 3). In the proposed method, a global vector (GV) that is a motion vector between the entire current image and the entire reference image is obtained, a macroblock of the current image is searched within a search region determined according to the reliability of the GV, and a motion vector is obtained. Detected. In this method, the correlation degree between screens is obtained as a reliability GRV, and the position of the search window at the time of motion search is determined based on the numerical value of the reliability GRV.
Japanese Patent Laid-Open No. 02-219388 Japanese Patent Laid-Open No. 08-070458 JP 2005-354528 A

  However, the proposed methods according to Patent Document 1 and Patent Document 2 have the following problems.

  First, in the proposed method according to Patent Document 1, it is possible to maintain a constant image quality by keeping the SN ratio in each picture constant. Also in the proposed method according to Patent Document 2, the SN ratio and the code of each picture are maintained. It is possible to keep a constant image quality by considering the distribution.

  However, in these methods, since the SN ratio is used as determination information for determining the target code amount, the code amount is determined not by the image before encoding but by the image after encoding. Therefore, for example, an image with few high-frequency components due to camera panning or the like, but an image in which the camera is stationary and the high-frequency components are greatly increased, or an image in which something enters the screen suddenly changes. Is happening. In this case, the signal-to-noise ratio is significantly reduced by encoding, and noise such as block noise is likely to occur. Therefore, even if an attempt is made to determine the target code amount with a constant SN ratio, it is difficult to determine an optimal code amount that does not generate noise.

  Thus, in the proposed method, it is difficult to set an optimal code amount that does not generate noise and obtain a decoded image with good image quality when the image changes. Therefore, an object of the present invention is to set an optimal code amount that does not generate noise when an image changes, and to obtain a decoded image with good image quality.

The present invention for solving the above problems is an image encoding device for encoding an encoding target image,
An encoding unit that orthogonally transforms an encoding target image, performs quantization processing, and encodes;
Decoding means for inversely quantizing the encoded image, performing inverse orthogonal transformation, and decoding ;
A global vector computing unit that computes a global vector that is a motion vector between the encoding target image and an image immediately before the encoding target image, and calculates a global vector reliability that indicates a degree of correlation between the images;
An SN ratio calculating means for calculating an SN ratio using the encoding target image and a decoding result obtained by decoding the encoding result of the encoding target image by the encoding means ;
Setting means for setting a target S / N ratio indicating a target S / N ratio value;
The encoding means based on the difference between the set target SN ratio and the calculated SN ratio, and the ratio between the global vector reliability of the encoding target image and the global vector reliability of the immediately preceding image Rate control means for adjusting the bit rate of the encoded data output from
It is characterized by providing .

  According to the present invention, an optimum code amount that does not generate noise even when an image changes can be set by increasing the bit rate in accordance with the image change, and a decoded image with good image quality can be obtained. be able to.

  Hereinafter, embodiments of the invention will be described with reference to FIGS. 1 to 4 of the accompanying drawings. FIG. 1 is a diagram illustrating a configuration example of an image encoding device that realizes an encoding method corresponding to an embodiment of the invention. Specifically, the encoding system corresponds to MPEG (Moving Pictures of Experts Group) and H.264 / AVC (Advanced Video Coding). Therefore, the image encoding apparatus can be realized as a video / audio signal recording apparatus such as a digital video camera. FIG. 2 is a diagram illustrating an example of image rearrangement. FIG. 3 is a flowchart illustrating an example of processing executed by each processing unit surrounded by a dotted line 120 of the image encoding device in FIG. FIG. 4 is a flowchart showing an example of rate control processing corresponding to the embodiment of the invention.

  First, in FIG. 1, an input signal 101 is an input signal to the image coding apparatus, and an image signal (CCD, CMOS, etc.) provided in the image coding apparatus or a video signal from a line input terminal corresponds to this. To do. The input signal 101 is input in a state of being divided into predetermined blocks. The block is, for example, a block such as 16 × 16 or 8 × 8 in MPEG, and the size is determined according to the encoding method. In this specification, this block is called a “macro block”.

  The image rearrangement unit 102 is a processing unit that changes the order of input images and outputs the images to a subsequent processing unit. The image rearrangement unit 102 includes an internal memory, and images input in the order of # 1, # 2, # 3,... As shown in FIG. .. Managing the memory so that it is output in the order of

  The switch 103 is a switch for switching between the output from the image rearrangement unit 102 and the output from the subtracter 114 in accordance with the picture type of the encoding target image. The DCT unit 104 is a processing unit that performs orthogonal transform (DCT). The quantization unit 105 is a processing unit that performs quantization processing on the orthogonal transform output coefficient output from the DCT unit 104. The variable length coding unit 106 is a processing unit that performs variable length coding processing on the quantization result output from the quantization unit 105.

  The buffer 107 is a buffer for temporarily storing the encoded data output from the variable length encoding unit 106, and outputs the encoded data to the output terminal 118 and the rate control unit 116. The inverse quantization unit 108 is a processing unit that performs an inverse quantization process on the quantization result in the quantization unit 105. The IDCT unit 109 is a processing unit that performs inverse orthogonal transform (IDCT) on the inverse quantization processing result. The adder 110 is an arithmetic unit that adds the decoded data obtained as a decoding result by the inverse orthogonal transform and the predicted image data output from the motion compensation prediction unit 112, and outputs a local decoded image.

  The switch 111 is a switch for supplying predicted image data from the motion compensation prediction unit 112 to the adder 110 according to the picture type of the encoding target image. The motion compensation prediction unit 112 is a processing unit that performs motion compensation prediction and generates predicted image data based on the output from the image rearrangement unit 102 and the output from the adder 110. The SN ratio calculation unit 113 is a processing unit that calculates an SN ratio using the output from the adder 110 and the output from the image rearrangement unit 102.

  The subtractor 114 is a calculation unit that performs a subtraction process between the output from the image rearrangement unit 102 and the predicted image data from the motion compensation prediction unit 112. The global vector calculation unit 115 is a processing unit that calculates a global vector based on the input signal 101. The rate control unit 116 is a processing unit that determines the target bit rate of the GOP to be encoded and the target code amount of the picture. The quantization control unit 117 is a processing unit that determines the quantization coefficient of the macroblock based on the target code amount of the picture determined by the rate control unit 116. The output terminal 118 is an output terminal that outputs encoded data temporarily stored in the buffer 107.

The dotted line region 120 includes a switch 103, a DCT unit 104, a quantization unit 105, an inverse quantization unit 108, an IDCT unit 109, an adder 110, a switch 111, a motion compensation prediction unit 112, an SN ratio calculation unit 113, and a subtractor. 114.

Next, the operation of each block in the dotted line area 120 of FIG. 1 will be described with reference to FIG.

  First, in step S301, the picture type is determined. If the picture type is an I picture (“YES” in step S301), the process proceeds to step S302 where the switch 103 is set to the A side and the switch 111 is turned OFF. Thereafter, the process proceeds to step S305.

  On the other hand, if the picture type is a B picture or P picture other than the I picture (“NO” in step S301), the process proceeds to step S303, the switch 103 is set to the B side, and the switch 111 is turned ON. In the subsequent step S304, motion compensation prediction unit 112 performs motion search to generate predicted image data, and subtracter 114 performs subtraction processing between the predicted image data and the input image to generate a difference value signal.

  Next, in step S305, orthogonal transformation is performed by the DCT unit 104 on a macroblock basis of the input signal, and the quantization unit 105 uses the quantization scale determined by the quantization control unit 117 to quantize the orthogonal transformation output coefficient. To generate encoded data. Here, the quantization scale, which is a quantization parameter, can be calculated by performing a process corresponding to STEP2 of TM5, and thus description thereof is omitted here.

  In the subsequent step S306, the quantized data generated in step S305 is subjected to inverse transform by the inverse quantization unit 108 and the IDCT unit 109 to generate decoded data as a decoding result. In the case of an I picture, a local decoded image can be obtained by this inverse transformation.

  In subsequent step S307, the picture type is determined in the same manner as in step S301. If the picture type is an I picture (“YES” in step S307), the process proceeds to step S310. On the other hand, if the picture type is a B picture or P picture other than the I picture (“NO” in step S307), the process proceeds to step S308. In step S308, the adder 110 performs an addition process of the predicted image data subtracted by the subtractor 114 and the decoded data obtained by the inverse transformation to generate a local decoded image of P picture or B picture.

  Next, in step S309, it is determined whether or not the picture type is a P picture. If it is a P picture (“YES” in step S309), the process proceeds to step S310. On the other hand, in the case of a B picture (“NO” in step S309), the process proceeds to step S311.

  In subsequent step S310, the generated local decoded image is stored in the motion compensation prediction unit 112 in order to serve as a reference image. In step S311, the SN ratio calculation unit 113 calculates the SN ratio between the input image and the local decoded image. Next, the process proceeds to step S312, and it is determined whether or not the encoding process has been completed for all the pictures. If completed ("YES" in step S312), this process ends. On the other hand, if there are still pictures to be encoded (“YES” in step S312), the process returns to step S301 to continue the processing.

  Returning to FIG. 1, the operation of processing blocks other than the dotted line area 120 will be described. The data output from the quantization unit 105 is input to the variable length encoding unit 106 and subjected to variable length encoding. The variable-length encoded data is input to the buffer 107 and output from the output terminal 118. Also, information such as the generated code amount and quantization coefficient of the encoded picture and the SN ratio calculated by the SN ratio calculation unit 113 are input from the buffer 107 to the rate control unit 116.

  Further, global vector calculation section 115 calculates global vector reliability GRV and outputs it to rate control section 116. An outline of a method of calculating the global vector reliability GRV in the global vector calculation unit 115 will be described below.

ここで、Ｓcur（ｍ，ｎ）は現在のピクチャでの（ｍ，ｎ）番目の画素値、Ｓref（ｍ，ｎ）は参照ピクチャでの（ｍ，ｎ）番目の画素値を示す。（ｉ，ｊ）は参照ピクチャに対する現在のピクチャの空間的な位置をそれぞれ示している。本実施形態では、参照ピクチャを現ピクチャの１つ前のピクチャとする。 First, the global vector is a spatial position difference (that is, a shift amount between pictures) between pictures (between an encoding target image and an immediately preceding image) input in the display order at the time of moving image reproduction (i. , j). That is, the global vector is a parameter that represents the overall motion between pictures or between wide areas (such as slices) smaller than a picture. In order to estimate the global vector having the maximum correlation, the following evaluation functions such as MSE (Mean Square Error) (Equation 1) and MAE (Mean Absolute Error) (Equation 2) are used. Alternatively, MAD (Mean Absolute Difference) may be used.

Here, Scur (m, n) represents the (m, n) th pixel value in the current picture, and Sref (m, n) represents the (m, n) th pixel value in the reference picture. (I, j) indicate the spatial position of the current picture with respect to the reference picture. In this embodiment, the reference picture is the picture immediately before the current picture.

  However, if M and N are the number of horizontal and vertical pixels in one picture, m = k × q and n = 1 × r, where k and l are 0 ≦ m ≦ M, 1 ≦ k ≦ M, 0 ≦ It is a natural number satisfying n ≦ N and 1 ≦ l ≦ N. Q and R satisfy M−k ≦ Q ≦ M and N−l ≦ R ≦ N.

  This evaluation function is based on the difference in pixel values, and determines the vector having the smallest MAE value or MSE value as a global vector. When the MAE value is taken as an example, the reference picture is shifted by one pixel in a predetermined direction, and an average of the sum of the MAE values is taken for each pixel moving distance. The amount of movement when the average MAE value is the minimum is the global vector selection criterion. This process is also performed for other directions orthogonal to a predetermined direction, for example, and if a movement amount that minimizes the average MAE value is obtained in this direction, a global vector is determined from the two movement amounts and the movement direction. Can do.

  Further, the minimum MAE value or MSE value obtained at this time is defined as a global vector reliability GRV (Global vector Reliable Value).

In this way, global vector calculation section 115 calculates global vector reliability GRV representing the degree of correlation between images, and outputs it to rate control section 116.

  The rate control unit 116 performs a process of determining a bit rate based on each input information so as not to generate noise. Details of processing in the rate control unit 116 will be described below with reference to the flowchart of FIG. FIG. 4 is a flowchart showing an example of processing for determining the bit rate in the rate control unit 116.

  First, in step S401, the target SN ratio (Tsnr) is set, and further, the global vector reliability (GRV (n)) input from the global vector calculation unit 115 is set. Here, “n” is an arbitrary number representing the picture number, and here, a value corresponding to the picture number of the current image to be processed is set.

  Next, in step S402, an average SNR (Asnr) of 1 GOP is calculated. This average SN ratio (Asnr) can be calculated, for example, as an average of the SN ratios for 1 GOP obtained by the SN ratio calculation unit 113. Further, based on the SN ratio obtained by the SN ratio calculation unit 113 for each picture type, an average SN ratio (Asnr) of 1 GOP can be predicted based on an average of the SN ratio. Note that the calculation method of the average SN ratio itself is not an essential feature of the invention, and therefore the calculation method is not limited to the two methods described above. Therefore, if there is another method that can be used as a method for obtaining the average signal-to-noise ratio of 1 GOP, it can also be used.

  In subsequent step S403, the target SN ratio (Tsnr) is compared with the average SN ratio (Asnr). If the average SN ratio (Asnr) is larger than the target SN ratio (Tsnr) (“YES” in step S403), the process proceeds to step S404. On the other hand, when the target SN ratio (Tsnr) is equal to or greater than the average SN ratio (Asnr) (“NO” in step S403), the process proceeds to step S405.

  In step S404, it is further determined whether or not the average SN ratio (Asnr) exceeds the target SN ratio (Tsnr) above the first threshold Th1. If the average SN ratio (Asnr) exceeds the target SN ratio (Tsnr) above the first threshold Th1 (“YES” in step S404), the process proceeds to step S406. On the other hand, if the average SN ratio (Asnr) does not exceed the target SN ratio (Tsnr) above the first threshold Th1 (“NO” in step S404), the process proceeds to step S408.

In step S406, (Asnr−Tsnr) × α is subtracted from the current rate (Rate) to calculate a new rate (Rate ⁻ ), and the process proceeds to step S408. Here, α is an arbitrary coefficient calculated from the average bit rate in VBR (variable bit rate). When the average S / N ratio (Asnr) greatly exceeds the target S / N ratio (Tsnr), the code amount is excessively given, and the target S / N ratio is exceeded even if the rate is lowered. Therefore, in step S406, processing for reducing the rate is performed.

For example, consider the case where Asnr = 45.0 dB, Tsnr = 40.0 dB, Th1 = 2, Rate = 7000000 bps, α = 200000 as numerical values. In this case, the average SN ratio (Asnr) exceeds the target SN ratio (Tsnr) by 5 dB, and this amount is larger than the first threshold Th1. Therefore, by performing the process of lowering the rate by the above calculation, the new rate (Rate ^-) to the 6000000Bps.

  Next, the process after step S405 is demonstrated. In step S405, it is further determined whether or not the target SN ratio (Tsnr) exceeds the average SN ratio (Asnr) above the second threshold Th2. If the target SN ratio (Tsnr) exceeds the average SN ratio (Asnr) above the second threshold Th2 (“YES” in step S405), the process proceeds to step S407. On the other hand, when the target SN ratio (Tsnr) does not exceed the average SN ratio (Asnr) above the second threshold Th2 (“NO” in step S405), the process proceeds to step S408.

In step S407, (Tsnr−Asnr) × β is added to the current rate (Rate) to calculate a new rate (Rate ⁺ ), and the process proceeds to step S408. Here, β is an arbitrary coefficient calculated from the average bit rate in VBR (variable bit rate). When the target S / N ratio (Tsnr) greatly exceeds the average S / N ratio (Asnr), the code amount is insufficient and the target S / N ratio cannot be exceeded unless the rate is increased. Therefore, in step S407, processing for increasing the rate is performed.

For example, consider the case where Asnr = 35.0 dB, Tsnr = 40.0 dB, Th1 = 2, Rate = 7000000 bps, β = 200000. In this case, the target SN ratio (Tsnr) exceeds the average SN ratio (Asnr) by 5 dB, and this amount is larger than the second threshold value Th2. Therefore, the rate is increased by the above calculation, and the new rate (Rate ⁺ ) is set to 8000000 bps.

  In step S408, the rate of change RGRV is calculated from the global vector reliability GRV (n) of the current picture to be processed and the global vector reliability GRV (n-1) of the previous picture. Here, the rate of change RGRV can be calculated by RGRV = GRV (n) / GRV (n−1).

  Next, in step S409, it is determined whether the rate of change RGRV (Ratio GRV) is greater than a third threshold value ThR. If the change rate RGRV is larger than the third threshold ThR (“YES” in step S409), the process proceeds to step S410. On the other hand, when the rate of change RGRV is not greater than the third threshold ThR (“NO” in step S409), the present process ends.

  In step S410, an operation of adding (RGRV-1) * γ * Rate to the current rate (Rate) is performed to calculate a new rate (Rate +) with an increased rate, and the process ends. Note that the third threshold ThR is a number equal to or greater than 1, and γ is an arbitrary coefficient calculated from the average bit rate in the VBR.

  As described above, when the rate of change RGRV is larger than the third threshold ThR, the correlation between the screens is lowered. The global vector reliability indicates the correlation between the screens. When the reliability is higher than that of the previous picture, that is, when the change rate RGRV is 1 or more, the correlation between the screens decreases, and the difference between the screens is reduced. Means to grow. Therefore, if the code amount is not increased, the image quality is lowered. For this reason, it is necessary to increase the amount of code according to the amount of change.

  For example, when the numerical values are ThR = 1.1, γ = 1, Rate = 6000000 bps, and RGVR = 1.2, the new rate is 720000 bps.

  The bit rate is calculated as described above, and the target code amount can be calculated from the above-described TM5 STEP1. The target code amount is input to the quantization control unit 117, and the quantization unit 105 is controlled by performing STEP2 and STEP3 of TM5.

  The rate calculation formula described above is merely an example, and the rate increase / decrease method is not limited to the above formula. In the above description, the case where both the SN ratio and the global vector reliability are used has been described, but only one of them may be used. Further, the rate can be controlled by another arithmetic expression using the average SN ratio (Asnr), the target SN ratio (Tsnr), the global vector reliability GRV, or the change rate RGRV.

  By performing the above processing, even when a large change occurs between frames or when an image with a low SN ratio exists, the state is detected before encoding and the target code amount is adjusted. The image quality can be improved. Therefore, even if an image with a small amount of high-frequency components due to panning, etc. is an image in which the high-frequency components are greatly increased due to camera stills or an image in which an object suddenly enters the screen, the target code amount is adjusted. High-quality encoding processing can be performed.

[Other Embodiments]
Note that the present invention can be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, and a printer), and a device (for example, a copying machine and a facsimile device) including a single device. You may apply to.

  The object of the present invention can also be achieved by supplying, to a system, a storage medium that records the code of a computer program that realizes the functions described above, and the system reads and executes the code of the computer program. In this case, the computer program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the computer program code constitutes the present invention. In addition, the operating system (OS) running on the computer performs part or all of the actual processing based on the code instruction of the program, and the above-described functions are realized by the processing. .

  Furthermore, you may implement | achieve with the following forms. That is, the computer program code read from the storage medium is written into a memory provided in a function expansion card inserted into the computer or a function expansion unit connected to the computer. Then, based on the instruction of the code of the computer program, the above-described functions are realized by the CPU or the like provided in the function expansion card or function expansion unit performing part or all of the actual processing.

  When the present invention is applied to the above storage medium, the computer program code corresponding to the flowchart described above is stored in the storage medium.

It is a figure which shows the structural example of the image coding apparatus which implement | achieves the encoding method corresponding to embodiment of invention. It is a figure which shows an example of image rearrangement corresponding to embodiment of invention. It is a flowchart which shows an example of the process performed by each process part enclosed with the dotted line 120 of the image coding apparatus of FIG. 1 corresponding to embodiment of invention. It is a flowchart which shows an example of the rate control process corresponding to embodiment of invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 ... Input terminal 102 ... Image rearrangement part 103 ... Switch 104 ... DCT part 105 ... Quantization part 106 ... Variable length encoding part 107 ... Buffer 108 ... Inverse quantization unit 109 ... IDCT unit 110 ... adder 111 ... switch 112 ... motion compensation prediction unit 113 ... SN ratio calculation unit 114 ... subtractor 115 ... global vector calculation Unit 116 ... rate control unit 117 ... quantization control unit 118 ... output terminal

Claims (5)

An image encoding device for encoding image data,
An encoding unit that orthogonally transforms an encoding target image, performs quantization processing, and encodes;
Decoding means for inversely quantizing the encoded image, performing inverse orthogonal transformation, and decoding ;
A global vector computing unit that computes a global vector that is a motion vector between the encoding target image and an image immediately before the encoding target image, and calculates a global vector reliability that indicates a degree of correlation between the images;
An SN ratio calculating means for calculating an SN ratio using the encoding target image and a decoding result obtained by decoding the encoding result of the encoding target image by the encoding means ;
Setting means for setting a target S / N ratio indicating a target S / N ratio value;
The encoding means based on the difference between the set target SN ratio and the calculated SN ratio, and the ratio between the global vector reliability of the encoding target image and the global vector reliability of the immediately preceding image Rate control means for adjusting the bit rate of the encoded data output from
Image encoding apparatus comprising: a. The rate control means includes
When the calculated SN ratio is larger than the target SN ratio, the difference between the calculated SN ratio and the target SN ratio is compared with a first threshold value, and the difference is larger than the first threshold value. If so, lower the bit rate,
When the calculated SN ratio is not larger than the target SN ratio, the difference between the target SN ratio and the calculated SN ratio is compared with a second threshold value, and the difference is larger than the second threshold value. The image encoding apparatus according to claim 1, wherein in the case, the bit rate is increased. The rate control means includes
A ratio between the global vector reliability of the encoding target image and the global vector reliability of the immediately preceding image is compared with a third threshold, and the bit rate is increased when the ratio is larger than the third threshold. The image coding apparatus according to claim 1 or 2, wherein A control method for an image encoding device for encoding image data, comprising:
An encoding step in which an encoding unit orthogonally transforms an encoding target image, performs quantization processing, and encodes;
A decoding step in which the decoding means dequantizes the encoded image, performs inverse orthogonal transform, and decodes ;
A global vector for calculating a global vector reliability representing a degree of correlation between the images by calculating a global vector which is a motion vector between the encoding target image and an image immediately before the encoding target image. A calculation process;
An SN ratio calculating step in which an SN ratio calculating unit calculates an SN ratio using the encoding target image and a decoding result obtained by decoding the encoding result of the encoding target image in the encoding step in the decoding step; ,
A setting step in which the setting means sets a target SN ratio indicating a target SN ratio;
Rate control means based on the difference between the set target SN ratio and the calculated SN ratio and the ratio between the global vector reliability of the encoding target image and the global vector reliability of the immediately preceding image A rate control step of adjusting the bit rate of the encoded data output in the encoding step;
A method for controlling an image encoding device comprising:   A computer program for causing a computer to function as the image encoding device according to any one of claims 1 to 3.

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