JPH042276A - Picture signal compression coding device - Google Patents

Abstract

PURPOSE:To make the coded data quantity constant by calculating an adaptive activity taking a weight in response to the DC component into account and deciding a bit quantity shared to a block. CONSTITUTION:An output from a DC coding section 50 is inputted to an area discrimination section 56 and a DC component of a luminance signal Y and color difference signals Cr, Cb is outputted from a Dc coding section 50. The area discrimination section 56 discriminates in which of color coordinate the signal component exists and where the region of the color represented by the signal component exists, an output (g) from the area discrimination section 56 is fed to a lookup table 53 and the lookup table 53 outputs a weight in response to the discrimination output (g) from the area discrimination section 56. Then the bit share of a coded data to each block is implemented according to an adaptive activity in which the DC component, that is, the weight taking the luminance and color into account multiplied with the activity for each block. Thus, the coded picture data quantity is made constant.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to an image signal compression encoding device, and more particularly to an image signal compression encoding device that makes the amount of data of a compression encoded image constant.

11 string l When storing digital image data such as image data taken by an electronic still camera in memory, in order to reduce the amount of data and the storage capacity of the memory,
Various compression encoding methods are used. In particular, two-dimensional orthogonal transform encoding is widely used because it can perform encoding at a high compression rate and can also suppress image distortion caused by encoding.

In such two-dimensional orthogonal transform encoding, image data is divided into a predetermined number of blocks, and the image data in each block is two-dimensional orthogonally transformed. , is compared with a predetermined threshold, and the portion below the threshold is truncated (coefficient truncation). As a result, the conversion coefficients below the threshold are then
Processed as 0 data. Next, the transform coefficients whose coefficients have been truncated are divided by a predetermined quantization step value, that is, a normalization coefficient, and quantization, that is, normalization, is performed according to the step width. This gives the value of the conversion factor,
In other words, the dynamic range of amplitude can be suppressed.

In such two-dimensional orthogonal transform encoding, if the above normalization coefficient is normalized and encoded as a constant value, the amount of encoded data will differ depending on the image data, making it inconvenient to record it in memory. Met.

In other words, when normalizing and encoding is performed using a certain normalization coefficient, image data containing many high frequency components will require a large amount of encoded data, and image data containing many low frequency components will require a large amount of encoded data. The amount of encoded data is reduced. Such a difference in the amount of encoded data can reach 5 to IO times, which is inconvenient when recording in a memory of a certain capacity.

For example, as disclosed in Japanese Patent Application No. 63-313840 of the present applicant, the extent to which high frequency components are included in each divided block, so-called activity, is calculated, and these are added to calculate the activity of the block. Calculate the total value, set the transformation coefficient based on this total value, perform normalization, and distribute the amount of encoded data to each block according to the activity value of each block relative to the total activity value, and output. The amount of encoded data is kept constant.

However, when determining the amount of encoded data to be distributed to each block based on the activity value of each block relative to the total activity value, there is a drawback that the image deteriorates significantly when encoded with high compression. be. For example, a person's face photographed against the light has little activity, so if the above method is used, the amount of encoded data allocated will be small, resulting in a highly distorted and unsightly image. There is a problem in that even when a specific part is important as an image, it cannot be taken into account.

Purpose The present invention solves such problems, and performs normalization according to the image to be compressed during normalization and encoding after two-dimensional orthogonal transformation, so that the amount of encoded image data becomes constant. It is an object of the present invention to provide an image signal compression encoding device that prevents image deterioration in a specific portion of an image.

Reach! According to the present invention, an image signal compression encoding device that divides digital image data constituting one screen into a plurality of blocks and performs two-dimensional orthogonal transform encoding on the image data of each block is configured to orthogonal transformation means for two-dimensional orthogonal transformation of digital image data divided into blocks; normalization means for normalizing the data orthogonally transformed by the orthogonal transformation means; and encoding the data normalized by the normalization means. An encoding means, a block activity calculation means for calculating the activity of the image data for each divided block, and a weight calculation means for calculating the weight of each block for the activity based on the DC component of the image data for each divided block. and adaptive activity calculation means for calculating the adaptive activity for each block from the activity for each block calculated by the block activity calculation means and the weight for each block calculated by the weight calculation means, and the adaptive activity calculated by the adaptive activity calculation means. The adaptive activity adding means adds the adaptive activity for each block, and the adaptive activity is allocated to each block based on the ratio of the adaptive activity for each block calculated by the adaptive activity calculating means to the total value of the adaptive activity calculated by the adaptive activity adding means. encoded data amount allocating means for calculating the amount of encoded data to be encoded; and encoding output control means for limiting the amount of output data from the encoding means according to the output from the encoded data amount allocating means; The conversion output control means is
The amount of encoded data distributed to each block output from the encoded data amount distribution means is compared with the amount of output data from the encoding means, and the amount of output data from the encoding means is distributed to each block. The amount of output data from the encoding means is limited so that it falls within the range of the amount of encoded data.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of an image signal compression encoding apparatus according to the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 shows an embodiment of an image signal compression encoding device according to the present invention.

This device has a blocking section 12. Block part 12
is constituted by a frame buffer, and one frame worth of still image data carried by the electronic still camera is inputted through the input terminal IO and stored. The image data for l frames stored in the blocking section 12 is divided into a plurality of blocks, read out block by block, and sent to the two-dimensional orthogonal transformation section 14. The image data stored in the blocking unit 12 is also divided into DC fD for each block.
c) The component is read out and sent to the DC encoder 50.

The two-dimensional orthogonal transform unit 14 performs two-dimensional orthogonal transform on the image pig for each block. As the two-dimensional orthogonal transformation, well-known orthogonal transformations such as discrete cosine transformation and Hadamard transformation are used. The image data for each block that has been subjected to two-dimensional orthogonal transformation in the two-dimensional orthogonal transformation unit 14 is arranged vertically and horizontally, with low-order data arranged in the upper left portion and higher-order data moving toward the lower right. The output of the two-dimensional orthogonal transform section 14 is sent to the normalization section 16. Note that a direct current (DC) component of data subjected to two-dimensional orthogonal transformation in the two-dimensional orthogonal transformation unit 14 may be sent to the DC encoding unit 50.

The normalization unit 16 performs normalization after truncating the coefficients of the image data subjected to the two-dimensional orthogonal transformation in the two-dimensional orthogonal transformation unit 14, that is, the transformation coefficients. Coefficient truncation compares orthogonally transformed transform coefficients with a predetermined threshold,
Normalization, which cuts off the part below the threshold value, divides the truncated transform coefficient by a predetermined quantization step value, that is, the normalization coefficient α, and calculates the normalization coefficient a.
This method performs quantization using The normalization coefficient α is determined from a lookup table based on the sum of activities for each block, as described later.

The image data for each block output from the blocking section 12 is also sent to the block activity calculating section 20. The block activity calculation unit 20 calculates the activity for each block, that is, the extent to which the block contains image data of high frequency components.

Calculation of activities ACTfi, , jl for each block is performed when the divided blocks are calculated, for example, in FIGS.
As shown in the figure, when it is composed of 8x8 pixels,
If the pixel data is X fi+, jll) (where k, 1=o...7), it is calculated by the following formula. Here, DC(i, jl = 1/64- ΣΣX (i+
It is jllll.

That is, according to this formula, the average value DCfi, .

When calculating the activity using the above formula, DC
fi, j) can be obtained by adding each pixel data and dividing the added data by 64, so it can be constructed only by an adder and data shifting. Also, ACTT
i, jl are obtained using the obtained DC (i, jl) by an absolute value conversion circuit and an adder. Therefore, multipliers and dividers are not required in calculating the activity.

To calculate the activity for each block, for example, divide the block into four sub-blocks as shown in Figure 7,
It may be determined by summing the activities of each sub-block. In this case, the activity ACT(i, jl) of the block is determined by the following formula.

ACTfi, j) = Σ Σ l X (i+, jl11 - DC(i, j, 01+ I
I X (to i+4+, jllll -DCfi, j
, l)+ΣX l X fi+, jl4+ll
−DC (i, j, 2) + X X I X (i
+4+, jl4+l) -DCfi, j, 3) In this equation, the first to fourth terms represent the extent to which high frequency components are included in the image data constituting subblocks 1 to 4, respectively. There is. For example, the first term in the above equation is the sum of the absolute values of the differences between each image data constituting sub-block l and the average value of the image data within sub-block 1. This represents the degree of high frequency components contained within sub-block 1.

By dividing the block into sub-blocks in this manner, determining the extent to which high-frequency components are included in each sub-block, and adding these, the activity of the block can be accurately calculated. That is, since the level of high frequency components is calculated for each sub-block rather than for the block as a whole, the activity of the block can be calculated more accurately.

Even in the calculation of such activities.

Similar to calculating the overall block activity above,
Does not require multipliers and dividers.

Calculation of activity for each block may be performed using a filter as shown in FIGS. 8A to 8C.

These filters 80 are sequentially moved from the upper left of the block in the direction of the arrows as shown in FIG.
The activity of the block is obtained by summing the values of the pixel data output from the block. For example, if the filter 80 in FIG. 8A is located at the upper left end of the block, the first
Pixel X i+1 in the θ diagram. jl1 Value multiplied by d8, X
i,,jXi+1. j, Xi+2. j,
Xi, j+], Xi+2. ,i+IXi,j
l2, Xi+1. jl2, Xi+2. jl2
Knee multiplied by 1 is output and these values are summed. If the values of these nine pixel data are the same, that is, if there is no change in the pixel and it is a DC component, the total value of the nine pixel data output from the filter 80 will be 0.6 Therefore, , by moving such a filter 80 to scan the block and summing the output values, the activity of the block can be obtained. For example, depending on the frequency component to be emphasized when determining the activity,
The filters shown in figures A to 80 may be selected.

Calculation of this activity also does not require multipliers and dividers.

As described above, the block activity calculation unit 20
calculates the activity for each block and outputs the value to the multiplier 54. The multiplier 54 also includes a looker.
The weight Wij data is sent from the embedded table 52.

The DC encoding unit 50 encodes the DC component data DCii, j) sent from the blocking unit 12. The data encoded by the DC encoder 50 is sent to a selector 60 and a lookup table fLUTl 52. As shown in FIGS. 3A and 3B, the lookup table 52 stores weight WIJ data corresponding to the DC component data DC(i,,j) sent from the DC encoder 50. . This weight Wij is multiplied by the activity ACTfij) for each block, as described later, and is used for allocating encoded data for each block.

In the case of the look-up table data shown in FIG. 3A, the weight WiJ is constant regardless of the value of the DC component data DCii,j). Therefore, in this case, the activity ACTi for each block will be explained later.
ij) is used to allocate encoded data for each block.

In the case of the lookup table data shown in FIG. 3B, when the value of the DC component data DCfi, , j) is small,
That is, the weight Wli is set to be large when the brightness is dark. If the amount of encoded data is allocated by multiplying the activity ACTlij by such a weight Wij, more bits of the encoded data will be allocated to areas with low brightness, such as the area of a backlit person, and the image quality will deteriorate. Improved.

The multiplier 54 multiplies the activity ACTli,jl for each block from the block activity calculation unit 20 by the weight Wlj sent from the lookup table, and calculates the adaptive activity AACT(ijl).

AACT (ij) = W i,j HACT (i
, il If the adaptive activity AACT (ijl) for each block calculated in this way is used to allocate the amount of encoded data for each block as described below, the value of DC (i, , j) as described above, For example, since more bits are allocated to dark areas, more bits are allocated to areas such as the face of a person photographed in backlight, resulting in an image with no noticeable distortion even at high compression.

The output AACT from the multiplier 54 (ijl is the output from the adder 26
and is output to the bit allocation calculation section 40.

The adder 26 calculates the total value of the adaptive activities AACT(ijl is added and the adaptive activities AACTfi,i) for each block sent from the multiplier 54. The adder 26 adds the total value of the adaptive activities AACTfijl to the normalization coefficient setting section 22 and the bit allocation calculation section 40.
Output to.

The normalization coefficient setting unit 22 sets the normalization coefficient according to the total value of the adaptive activities AACT (ijl) input from the adder 26. The normalization coefficient setting unit 22 sets the normalization coefficient according to the total value of the adaptive activities AACT (ijl) input from the adder 26. Using,
For example, the conversion is performed as shown in FIGS. 11A and 11B. According to the transformation shown in FIG. 11A, the normalization coefficient changes in proportion to the total value of the adaptive activities AACT(ij). The conversion shown in FIG. 11B is one in which the increase in the normalization coefficient is small relative to the increase in the total value of the adaptive activities AACT (ijl), and highly accurate encoding can be performed.

The normalization coefficient setting unit 22 outputs the normalization coefficient set in this way to the normalization unit 16.

The normalization unit 16 performs normalization using the normalization coefficients sent from the normalization coefficient setting unit 22. That is, the image data for each block is divided by the normalization coefficient. Since the normalization coefficient used for normalization is set based on the sum of the adaptive activities AACTlijl for each block as described above, it is common to the entire image, that is, for all blocks.

Note that in this normalization, instead of dividing the truncated transform coefficient by the value α of one selected normalization coefficient, the data stored in the weight table T as shown in FIG. and the normalization coefficient a may be used together. As for the conversion coefficient, the low-frequency component is important as data, and the high-frequency component is less important, so the weight table T shown in Figure 12 assigns a small value to the low-frequency component and a small value to the high-frequency component. A large value is assigned to , and the data in table T is normalized by dividing the truncated conversion coefficient by the value α・T obtained by multiplying the data in table T by the normalization coefficient α. You may also do so.

The normalized transform coefficients are arranged in blocks in the same way as the pixel data shown in FIG. 6, and are sequentially scanned in a zigzag pattern starting from the low frequency component as shown in FIG. Output.

The output of the normalization unit 16 is output to a two-dimensional Huffman encoding unit 28. The two-dimensional Huffman encoding unit 28 often has consecutive zeros in the normalized transform coefficients that are scanned and input in a zigzag manner as described above. Detect run length,
A run length of zero and an amplitude of non-zero are determined and subjected to two-dimensional Huffman encoding. The output from the two-dimensional Huffman encoding unit 28 is output to the separator 60 and is also sent to the code amount counting unit 44. il and
The adaptive activity AACT(
Using the total value of ij), the coded bits allocated to each block are calculated. The encoded bits allocated to each block are two-dimensional Huffman encoded for each block,
This is the number of bits that defines the point at which the AC component data output from the low frequency component is to be cut off, that is, the number of bits of encoded data to be output.

Coded bits bitfi,j) allocated to each block
is given by the following formula.

bitfi, jl = (total number of bits of the entire image x AA
cT (month)/total adaptive activity) + [remaining bits up to the previous block]... (11 In the above equation, "the total number of bits J of the entire image is the total number of bits J of the entire image composed of multiple blocks during encoding. i.e. 2 bits per block.
This is the number of bits that indicates how many bits are allocated to the entire image when dimensional Huffman encoded data is output in order from the low frequency component and the output of the data is stopped at a predetermined number of bits. This number of bits determines the amount of data that is compressed and encoded and output.

AACT(ijl is the adaptive activity for each block as described above, and is manually input from the multiplier 54.

The total adaptive activity is the sum of the block's adaptive activities AACT(i,i) sent from the adder 26.

Therefore, in the above equation (total number of bits of the entire image XAA(:
T(ij)/total adaptive activity) distributes the number of bits allocated to the entire image by the ratio of the adaptive activity AACTfijl for each block to the total value of the adaptive activities AACTlij) of the block.

[The remaining bits 3 up to the previous block are divided into the remaining bits up to the block immediately before the block for which the allocated encoded bits bitfi, jl are to be calculated, that is, the remaining bits up to the previous block. This is the difference between the number of bits and the number of bits actually encoded and output. For example, in the previous block, if the number of allocated bits is 50 bits and the actual number of bits encoded and output is 45 bits, the remaining bits are 50-45=5 bits.

By adding such surplus bits, the difference between the number of bits allocated to each block and the number of bits actually output is prevented from accumulating.

The encoded bits bitfi,jl to be allocated to each block, which are determined by the bit allocation calculation unit 40, may be determined by the following equation.

bit(i, jl = [total number of bits of entire image - Σ Σ
bit fk, II ] x AAC ding fi, il/
[Total adaptive activity - ΣΣAACTfijl]・
(2) In the above equation, ΣΣbit [k, 11 is a recurrence formula that indicates the sum of the number of bits allocated up to the previous block. Therefore, [total number of bits of the entire image - ΣΣbit
(k, 11 ] represents the total number of bits allocated to the remaining blocks. Also, ΣΣAACTfi old represents the sum of the adaptive activities of the blocks up to the previous block. Therefore, [Total adaptive activity - Σ
ΣAACT (ij) ] indicates the sum of the adaptation activities of the remaining blocks.

According to the above formula, the total number of bits allocated to the remaining blocks is distributed according to the ratio of the adaptive activity of that block to the sum of the adaptive activities of the remaining blocks. According to this formula, the coded bits bitii, j) divided into Qe by blocks are calculated by considering the number of bits allocated up to the previous block and the adaptive activities of the blocks up to the previous block. Therefore, the difference between the total number of bits allocated to each block and the total number of bits of the entire image becomes smaller than in the case of equation (1).

Coded bits bitfi,j) allocated to each block
may also be determined by the following formula.

biNi, jl = [total number of bits of the entire image - Σactual sent bits up to the previous block] xAAcTfijl/
[Total adaptation activity - ΣΣAACT(i, il]
(3) In the above equation, the actual sent bits up to the previous block Σ represent the sum of the number of bits actually encoded and output up to the previous block. Therefore, [total number of bits of the entire image - Σactual sending bits to the previous block]
Considering the number of bits actually encoded and output up to the previous block, t: represents the total number of bits allocated to the remaining blocks.

Therefore, according to the above formula, the total number of bits allocated to the remaining blocks, taking into account the number of bits actually encoded and output up to the previous block, can be calculated as follows: It is distributed according to the ratio of adaptation activities. According to this formula, the coded bit bit (i , j), the above i1
) There is no need to consider the remaining bits up to the previous block as in the +2+ formula.

The encoded bits bitfi, il distributed to each block output from the bit allocation calculation unit 40 are sent to the encoding stop determination unit 42. On the other hand, the encoded output from the two-dimensional Huffman encoding unit 28 is output to the code amount counting unit 44. The code amount counting unit 44 calculates the code amount of the output from the two-dimensional Huffman encoding unit 28 for each block, that is,
Count the cumulative number of bits. Code amount counting section 44
outputs data obtained by adding the number of bits of encoded data to be output next from the two-dimensional Huffman encoding unit 28 to the encoding stop determination unit 42.

The encoding stop determination unit 42 calculates the number of bits inputted from the code amount counting unit 44 and the encoded bits bitfi,j to be allocated to each block inputted from the bit allocation calculation unit 40.
Compare with l. When it is detected that the number of bits inputted from the code amount counting unit 44 exceeds the encoded bits bitii, jl inputted from the bit allocation calculation unit 40, a signal indicating that encoding output should be stopped is subjected to two-dimensional Huffman encoding. output to section 28. As a result, the two-dimensional Huffman encoding unit 28 stops outputting the encoded data corresponding to the number of bits added last in the code amount counting unit 44, that is, the encoded data to be output next, and outputs the encoded data. The number of bits of data to be processed does not exceed the encoded bits bit(i,,i) inputted from the bit allocation calculation unit 40. That is, the Huffman encoded output of the block is terminated up to the previous encoded data in which the encoded output data exceeds the allocated encoded bits.

The encoding stop determination unit 42 further determines the difference between the allocated encoded bits and the number of bits of encoded output data, that is, the remaining bits, and outputs it to the bit allocation calculation unit 40. The bit allocation calculation unit 40 uses the remaining bits when calculating the encoded bit bit (i, j) to be allocated according to the above formula (11f21).

The encoded AC component image data output from the two-dimensional Huffman encoding unit 28 is sent to the selector 60 .

The selector 60 selects the DC component data sent from the DC encoding section 50 and the AC component data sent from the two-dimensional Huffman encoding section 28 and outputs them to the output terminal 32. The data sent to the output terminal 32 is transmitted to a transmission line (not shown) or recorded on a recording medium such as a magnetic disk.

According to this device, the activity ACTfijl calculated for each block as described above is multiplied by the weight Wi,j to obtain the adaptive activity AACTfij), and this is used to allocate the amount of encoded data for each block. .

That is, the adaptation activity AACT(
The total value of ijl is determined, and based on this, a normalization coefficient α is set to perform normalization. Therefore, the normalization coefficient α is
Since the encoded image data is set to be a constant amount, it is easy to process the output data and it is convenient to store it in a memory.

This device calculates the adaptive activity AACT (adaptive activity AACT for each block for the total value of ijl)
The coded bits to be allocated to the coded output of each block are determined based on the ratio of (ij). The adaptive activity AACTli,il for each block is obtained by multiplying the activity ACTfi,jl for each block by a predetermined weight Wij, as described above. Therefore, since the number of bits allocated to each block is distributed by taking into account the activity of that block and the weight Wij, the data of each block is effectively encoded according to the activity of the block, and for example, the data of the luminance component is By increasing the weight Wij for dark areas, it is possible to allocate more bits to areas such as backlit parts of a person, thereby improving the image quality.

FIG. 2 shows another embodiment of the image signal compression encoding device according to the present invention.

The apparatus of this embodiment allocates more bits to a part of a particular color, for example, a flesh-colored part such as a person's face, to accurately represent this part.

Or, conversely, reduce the bit allocation to the human part,
In the case of a device that blurs this portion, the output from the DC encoding section 50 is input to the area determining section 56. The DC encoding unit 50 outputs a luminance signal Y and a color difference signal Cr for each block.

Each DC component of cb is output. Area determination unit 56
determines where these signal components are located in the color coordinates shown in FIG. 4, that is, the color region represented by the signal components. The region determination unit 56 determines whether the manually input signal belongs to a skin-colored region, for example. The output g from the area determination unit 56 is a function g (Y, Cr, Cb) of the input signal components Y, Cr, and Cb.6 For example, Yl<Y<Y2. Crl<Cr<Cr2C
When the condition bl<Cb<Cb2 is satisfied, it is determined that the area is within the skin color region shown in FIG. 4, and g=1 is output. In cases other than the above conditions, g=Q is output. The output g from the region determining section 56 is sent to the lookup table 52. The lookup table 52 is configured, for example, in FIG. 5A or in FIG.
A weight WiJ as shown in diagram B is output.

When using the lookup table shown in FIG. 5A, a large weight Wij value is output when the output g is 1. Therefore, since a large weight Wij is applied to the skin-colored portion, many bits are allocated to, for example, a person's face, and this portion becomes a high-quality image. On the contrary, the fifth
When using the look-up chain shown in Figure B, when the output g is 1, a small value of weight Wij is output.

Therefore, since the weight Wlj of the skin-colored portion is reduced, fewer bits are allocated to, for example, the face of a person, making it possible to blur the portion of the person.

Note that the region determination unit 56 is not limited to the skin color described above, and any other specific color may be set.
You can accurately express or blur the set color part.

In the above embodiment, bits of encoded data are allocated to each block by an adaptive activity that is obtained by multiplying the activity for each block by a DC component, that is, a weight that takes into account brightness and color. Bit allocation may also be performed. In this case, specific parts of brightness and color can be emphasized or blurred more strongly.

Effects According to the present invention, the compression encoding device calculates an adaptive activity that takes into account a weight corresponding to a DC component in the activity of a block, and thereby determines the amount of bits to be allocated to each block. Therefore, it is possible to perform compression encoding according to the frequency component, and also adjust the amount of bits allocated to a predetermined brightness area or a specific color area.
The amount of encoded data can be kept constant.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing one embodiment of the image signal compression encoding device according to the present invention, FIG. 2 is a block diagram showing another embodiment of the image signal compression encoding device according to the present invention, and FIG. 3A , FIG. 3B is a diagram showing the relationship between DC components of image data and weights, FIG. 4 is a diagram showing the relationship between signal components and color areas, and FIGS. 5A and 5B are area determination signals. FIG. 6 is a diagram showing the relationship between g and weight; FIG. 6 is a diagram showing an example of pixel data constituting a block; FIG. 7 is a diagram showing the division of a block into sub-blocks; FIG. 8A, FIG. 8B, FIG. 8C is a diagram showing an example of a filter used to calculate activity, FIG. 9 is a diagram showing a method of calculating activity using the filter, and FIG. 10 is a diagram showing an example of pixel data forming a block. , FIG. 11A and FIG. 11B are diagrams showing an example of a lookup table for converting the total value of activities into a normalization coefficient, FIG. 12 is a diagram showing an example of weight table data, and FIG. FIG. 6 is a diagram showing the order in which lengths and non-zero amplitudes are encoded. Explanation of r'''' in main part Two-dimensional orthogonal transform section Normalization section Block activity calculation section Normalization coefficient setting section Adder Two-dimensional Huffman encoding section Bit allocation calculation section, coding stop judgment section Code amount counting section Anal code Lookup Table Multiplier Area Judgment Unit Patent Applicant Fuji Photo Film Co., Ltd. Representative Person Number Ooyu Volcano Takao Daisetsu Figure 3A Figure 3B DC (ij) Figure Figure 5A Figure 5B Figure Figure Figure 10 ×1・j Xi+I, j X I+2, j Xi, jl Xin, ju Figure 11B Hourly Pity 1H Shift Figures 12 and 13

Claims (1)

[Claims] 1. An image signal compression encoding device that divides digital image data constituting one screen into a plurality of blocks and performs two-dimensional orthogonal transform encoding on the image data of each block, the device comprising: , orthogonal transformation means for two-dimensional orthogonal transformation of the digital image data divided into the plurality of blocks; normalization means for normalizing the data orthogonally transformed by the orthogonal transformation means; a block activity calculation means for calculating the activity of the image data for each of the divided blocks; and a block activity calculation means for calculating the activity of the image data for each of the divided blocks; weight calculation means for calculating a weight; and adaptive activity calculation for calculating an adaptive activity for each block from the activity for each block calculated by the block activity calculation means and the weight for each block calculated by the weight calculation means. means, adaptive activity adding means for adding the adaptive activity for each block calculated by the adaptive activity calculating means, and the adaptive activity for each block calculated by the adaptive activity calculating means and the adaptive activity calculated by the adaptive activity adding means. encoded data amount allocating means for calculating the amount of encoded data to be allocated to each block from the ratio to the total value of the adaptive activities; and encoding output control means for limiting the amount of output data from the means, the encoding output control means controlling the amount of encoded data distributed for each block output from the encoded data amount distribution means; , the output data amount from the encoding means is compared with the output data amount from the encoding means, and the output from the encoding means is determined so that the output data amount from the encoding means is within the range of the encoded data amount allocated to each block. An image signal compression encoding device characterized by limiting the amount of data. 2. The image signal compression encoding device according to claim 1, wherein the weight calculation means calculates the weight based on a DC luminance component of the image data for each block. 3. The image signal compression encoding device according to claim 1, wherein the weight calculation means calculates the weight based on a DC hue component of the image data for each block. 4. The apparatus according to claim 1, wherein the encoded data amount allocation means multiplies the encoded data amount of the entire image data by a ratio between the adaptive activity for each block and the total value of the adaptive activities. An image signal compression encoding apparatus characterized in that the amount of encoded data to be distributed to each block is calculated by adding the amount of remaining data of the previously encoded block.