JPH07296170A - Multidimensional multilevel image compressing and expanding system - Google Patents

Abstract

PURPOSE:To prevent the degradation of picture quality from occurring by moving a specified equal luminance line passing point coordinate to the central position of respective picture elements consisting of a specified luminance boundary provided by tracing the contour of a picture element at a specified luminance value in the case of compression. CONSTITUTION:The binarized output of a digital luminance signal outputted from an extracting part 5 for the luminance level information of signal processing parts 4-1-4-n starts scanning and when the first boundary is found out, with that point as a starting point, the contour of the picture element at the specified luminance value is started being traced. Then, the contour line information is transmitted. Next, at a contour line address list 8 to which the output signal (address strobe) of contour line information outputted from respective contour line tracers 7 at the signal processing parts 4-1-4-n and a contour line address output are supplied, the specified equal luminance line passing point coordinate is moved to the central position of respective picture elements forming the specified luminance boundary. The address output at the central position of respective picture elements outputted from the contour line address list 8 is supplied to a polygonal approximate address list 9.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a multi-dimensional multi-valued image compression / decompression system, and more particularly to pixel correspondence on the compression side and decompression side such as image transmission between different models, or frame correspondence on the time axis. The present invention relates to a multi-dimensional multi-valued image compression / expansion method capable of performing highly efficient image expansion in a system in which is not guaranteed.

[0002]

2. Description of the Related Art Various methods have been conventionally proposed for compression of image information. For example, when linear quantization (equal quantization) means is adopted in which the signal level is evenly divided for each sampled value of the digitalized image signal and the values included in each range are replaced with one representative value. It is said that 6 bits (64 gradations) to 8 bits (256 gradations) are generally required for a natural image when the difference between the representative point and the original value is not known.
In order to record a signal obtained by digitizing the image signal by the uniform quantization as described above, it is necessary to handle a large amount of information as described above for each sample value.

Therefore, even if the signal is encoded with a smaller amount of information, it is sensitive to the change in the part where the signal changes little and there is some error in the part where the signal changes drastically. It is difficult to detect the human visual and auditory characteristics, or by utilizing the correlation on the spatiotemporal axis of the information signal that is the target of recording, for example, after dividing the image into pixels, each pixel Use the height of the adjacent correlation of the luminance values to transmit a small number of the approximate values of the original information, or to transmit the pixel-to-pixel difference or the frame-to-frame difference, or to use the fact that there are few high frequency components. The digital data is compressed by applying various high-efficiency coding schemes that reduce the amount of information for each sample by reducing the frequency elements. Record, It has been conventionally practiced to restore an image by transmitting and transmitting, and by reproducing and receiving the digital data in which the amount of data is compressed as described above, and then expanding the data. As is well known.

[0004]

In the above-mentioned conventional general compression method of image information, it is important to restore the decomposed pixels satisfactorily. In many cases, the condition is that the number of pixels in the images (decompressed images) is the same. Therefore, when compression / decompression operation is performed between images with different numbers of pixels, pixel interpolation after decompression is performed separately. However, in the conventional compression method of image information, only true effective information is extracted and not restored, and it is a physical image constituent element to some extent. It means that the method depends on.

By the way, as described above, two pixels having different numbers of pixels are used.
As an example of a case where the pixel densities of two images are extremely different, for example, when an image captured by the image capturing device is used as a printing plate, the pixel density of the image captured by the image capturing device is one screen. The maximum pixel density per image is 500 (500 x 500), whereas the pixel density of an image on an electronic plate making machine is (thousands x thousands) per screen.
As described above, since it is an order of magnitude larger than the image obtained by the image pickup by the above-described image pickup apparatus, even if the compression / expansion method of the image information corresponding to the pixel as described above is not performed at all, an alias occurs due to the pixel enlargement. To do.

Further, when the interpolation is performed without performing the pixel enlargement as described above, since a vast interpolation area is filled with a known weighted average value of data, interpolation distortion may occur. Image quality deterioration cannot be avoided. Contrary to the above, when the pixel density of the original image is per one screen (several thousands × several thousands), the correlation between adjacent pixels is extremely high. Although compression is possible, the compression rate cannot be increased with the conventional image information compression method that requires the number of pixels between the original image and the restored image (decompressed image) to match, as described above. The drawback occurs.

In order to solve the above-mentioned problems, the applicant's company previously mentioned in Japanese Patent Application No. 5-39492, irrespective of whether the pixel density of an image targeted for image information processing is high or low, Only the characteristic points of the image are extracted to obtain the image data in which the image information is compressed, and when decompressing, the pixel restoration is not performed from the image data described above, but a new image is formed on another pixel density plane. So as to be able to draw, two-dimensionally distributed luminance information, and three-dimensionally distributed image information including a time axis in the image information of the two-dimensionally distributed luminance information. Is a positive or negative maximum point of curvature of the equiluminance line or the positive or negative maximum point of curvature of the equiluminance surface, or a straight line obtained by approximating the equiluminance line of the luminance function and the equiluminance line of the above luminance function. Or the error of the brightness function An error between a plane that is a plane approximation of the luminance plane and the equal luminance plane of the luminance function described above is defined as a feature point of the image that exceeds a predetermined threshold, and the position and the luminance value of the feature point of the image are described. When transmitting and recording, and using the position of the characteristic point and the luminance value for image restoration, the luminance information of pixels other than the characteristic point is determined by an interpolation plane or an interpolated solid determined by a plurality of neighboring characteristic points when expanding. The image information of the luminance information which is determined and which is three-dimensionally distributed including the time axis in the image information of the two-dimensionally distributed luminance information
Targeting a plurality of sets of dimensionally distributed luminance information, the positive and negative maximum values of the curvature of the equiluminance lines of the luminance function of each set, or a straight line that approximates the equiluminance lines of the luminance function of each set described above. With the point where the error between the above-mentioned brightness function and the isoluminance line exceeds a predetermined threshold value as a characteristic point of the image, the position and the luminance value of the characteristic point of the image described above are transmitted, recorded, and image restored. When used, a multidimensional image compression / expansion method is provided in which, when expanding, the luminance information of pixels other than the feature points is determined by an interpolated solid determined by a plurality of neighboring feature points.

The following is a description of the previously proposed multidimensional image compression / expansion method. Now, assuming that the brightness in the black and white still image is z, the horizontal direction of the screen is x, and the vertical direction is y, the image can be generally expressed by the following equation (1). z = f (x, y) (1) Further, if the time axis is t, the moving image can be expressed by the following equation (2). z = f
(X, y, t) (2) Here, if f is a multi-dimensional function, the brightness z in the image is expressed by the following equation (3).

[0009]

[Equation 1]

By the way, transmitting an image means
It can be said that the above-described brightness function determined on the image sending side is reproduced on the image receiving side, but in a general digital image transmission, the brightness function is not handled analytically, and as a so-called table function, All of the table values are transmitted. On the other hand, in conventional general compression transmission, high-efficiency coding using the adjacent correlation of the table value itself is performed, or the same measure is applied to the table value after orthogonal transformation. Although measures such as rubbing are taken, conventionally, there are few compression transmission systems that directly extract the feature value of the function from the analytical processing related to the luminance function.

Image information such as two-dimensional luminance information in a still image, or three-dimensional luminance information including a time axis in the two-dimensional luminance information is exemplified in FIG. Luminance line (contour line) {isoluminance surface in the case of three-dimensional luminance information} is extracted, and the extracted isoluminance line is extracted.
(Contour line) {Positive positive and negative maximum points of curvature of {3D luminance information}
Linear approximation of {equi-luminance surface for three-dimensional luminance information} (3
The error from the plane approximation in the case of dimensional luminance information} is
A point that exceeds a predetermined threshold value is used as a characteristic point of the image described above, and the position and the luminance value of the characteristic point of the image described above are used for transmission (recording) and image restoration, which affects the reproduction of the luminance function. A large amount of compression of the image information can be realized by rejecting the luminance information of a small number of pixels, and when the image information is expanded, the interpolation surface determined by the plurality of transmitted (recorded) neighboring feature points described above. , Or interpolated solids are used to perform high-quality image expansion.

That is, in the proposed multidimensional image compression / expansion method, first, the above-mentioned characteristic points extracted from an image when image information compression is performed on a still image, that is, isoluminance lines (contour lines of a luminance function). ) {Positive positive / negative maximum points of curvature of 3D luminance information}, or a straight line approximation of the above-mentioned isoluminance lines (contour lines) {equal luminance surface in the case of 3D luminance information} Regarding the feature points of the image in the case of extracting points where the error from (planar approximation in the case of three-dimensional luminance information) exceeds a predetermined threshold,
1. When the bend of the above-mentioned contour line (contour surface in the case of three-dimensional luminance information) before and after the pixel a under consideration exceeds a predetermined threshold angle,
The pixel a is determined to be a feature point. 2. With respect to a virtual straight line between a detected feature point pixel and a pixel traced in a certain direction along the contour line (contour plane in the case of three-dimensional luminance information) from the feature point pixel, It is determined that the pixel between the two pixels that has a distance exceeding a certain threshold distance is a feature point.

The characteristics of the target image for image information compression as described above are taken by taking the example of FIG. 26, which exemplifies the luminance distribution function in the two-dimensional screen in an arbitrary still image, by adopting the above-mentioned criterion. A specific example of extracting points is as follows. 26A illustrates one of the contour lines of the luminance distribution function in the two-dimensional screen, the extraction of the contour line of the luminance distribution function in the two-dimensional screen is as follows. It is done by procedure. FIG. 26
With reference to (b), the method of searching for points showing equal brightness will be described. In (b) of FIG. 26, (1) to (4) are four pixels, and the brightness values of the respective pixels (1) to (4) are H, L (H is a high brightness value, L is a low brightness value), and the point S at which the first extracted value is obtained is the starting point of contour line extraction. The S
Since the point is located between the pixel (1) and the pixel (4), the brightness value at the coordinate position is, for example, the brightness value corresponding to the brightness value of the pixel (1) and the brightness value of the pixel (4) described above. A proportional distribution value may be used.

Isoluminance lines (contour lines) obtained by connecting the points having the luminance value equal to the luminance value from the starting point S point to the point S described above.
In order to track the image, the sides (1)-(2), (2) -in the image shape indicated by the above-mentioned four pixels (1) to (4).
When the presence or absence of a point having the same brightness value (contour value) as the brightness value of the start point S is verified in the order of (3), (3)-(4), the above-mentioned contour value is the side (1)- (2) Detected at point M1 above. After the point M1 having the above-mentioned contour value is detected, the procedure described above is repeated to detect the next point M2 having the contour value. Go forward. In the extraction of the contour lines, the side where the contour lines have already intersected is excluded from the detection target (except for the start point S described above). As described above, by detecting the sequential points having a certain luminance value and the equal luminance value, one of the contour lines of the luminance distribution function in the two-dimensional screen as illustrated in FIG.
One is extracted.

One of the contour lines of the brightness distribution function in the two-dimensional screen
In FIG. 26A exemplifying two points, the path of the isoluminance lines (contour lines) formed by a series of isoluminance points sequentially traced from the S point which is the start point is suddenly changed. M6 is 1. of the criteria for determining the feature points described above. Is determined as a feature point (points M8, M14, M16, M18,
As for M20, 1. According to the above). After the point M8 indicating the equal brightness value is detected and the points of equal brightness value are sequentially tracked to reach the point M12, the point M10 at which the distance from the virtual straight line M8-M12 occurs is Although it is not a sudden change point in 2. Is determined as a feature point. This also applies to the points M12 and M12.
As described above, since the luminance distribution function in the two-dimensional screen is replaced by contour lines (contour lines), the image information is rejected, and the feature points of the contour lines are further aggregated. The image compression / expansion method enables transmission (recording) in a highly compressed state.

As described above, in the proposed multidimensional image compression / expansion method, the two-dimensional luminance function in the image which is the object of image information compression is replaced with the positional information and the luminance information of a few feature points. Accordingly, in order to obtain a reproduced image by decompressing (restoring) the image information transmitted (recorded) in a state in which the image information is highly compressed, the above-mentioned feature points correspond to the corresponding points ( It does not need to correspond to the original image and pixels)
The decompression method is adopted that determines the luminance value of and reduces the influence on the surrounding pixels in proportion to the distance from the feature point. The image information expansion as described above is performed by linear interpolation between feature points in one dimension, but the image information expansion in a multidimensional space is performed by plane interpolation or stereoscopic interpolation. Then, the principle will be described with reference to FIG.

FIG. 27 is a characteristic point S, M6, M8, M10, M12, M14, M16 shown in FIG. 26A obtained as described above with reference to FIG. , M18, M2
Contour lines (isoluminance lines) reproduced on the image memory on the reproducing side are included by using position information (addresses) of 0 and M22. In FIG. 27, the contour lines (contour lines of the M group) are the characteristic points S, M6, M8, M10, M12, M14, M16,
It is indicated by a dotted line that sequentially connects M18, M20, and M22. Further, in FIG. 27, the characteristic points Ni, Nj, Nk, Nl
The dotted line sequentially connecting the lines shows the contour line of the characteristic points of the N group different from the contour line of the characteristic points of the M group described above.

When the area between the contour lines of the M group and the contour line of the N group is filled with the brightness values indicated by the N group, the brightness values in the area surrounded by the contour lines of the M group are Due to a clear luminance step that occurs between the two, a so-called pseudo contour phenomenon occurs, which makes it impossible to obtain a high-quality expanded image. Therefore, in order to prevent the pseudo contour phenomenon as described above from occurring, the feature points belonging to the M group and the feature points belonging to the N group are represented by za = Σ (zi
/ Ri) / Σ (1 / ri) (A) Applies by plane interpolation, which is an approximate calculation of the above-mentioned expression (A).

Here, considering a specific pixel a in the decompressed screen,
The distance from the specific pixel a to the pixel of each feature point is r
i, the brightness value of the pixel of each feature point is zi, and α is a proportional constant, the brightness value zk of one feature point k among the feature points and the brightness value za of the pixel a. The relationship is expressed by the following interpolation formula (4). za = zk + αkrk (4) αkrk in the second term on the right side of the equation (4) represents the difference between the luminance value of the pixel a and the luminance value zk of the feature point k, The value of αk · rk is proportional to the distance r. The brightness value of the pixel a and the brightness value zk of the feature point k described above.
There is a positive / negative difference in the luminance value αk · rk between and, which is reflected in the proportional constant α, but the total sum of α in the entire interpolation space is zero. Then, Σαk = 0 (5)
When the general interpolation formula of the luminance value za of the pixel a is obtained by deleting the term of α from the above formula (4) in consideration of the condition of the formula (5), the above formula (A) is obtained. Be done. za = Σ (zi / ri) / Σ (1 / ri) (A)

The above equation (A) is used for the brightness values zi of all feature points.
And the distance r to the pixel a that is the interpolation target is known,
It shows that the brightness values of all the non-interpolated pixels (which may not correspond to the original image) in the screen can be obtained by interpolation. However, since the expression (A) exceeds the practical calculation amount as the number of feature points increases, the interpolated luminance value is approximately calculated by the interpolated surface determined by the three neighboring feature points surrounding the uninterpolated pixel. Since one plane is determined by three points in the space as is well known, an interpolating triangle can be obtained by grouping three neighboring feature points. Therefore, in FIG. 27, each three feature points “Ni, Nj, S”, “Nk, M6, S”, “Nj, Nk,
The luminance value of the pixel within each triangle formed by S "is
Each of them can be applied by plane interpolation by the approximation calculation that performs the above-mentioned formula (A).

Now, in order to determine the interpolation surface when performing the above-described plane interpolation, it is necessary to extract three feature points in the neighborhood. Next, referring to FIG. 29, the three feature points in the neighborhood are extracted. The principle of extracting feature points will be described. In FIG. 29, the pixels Mi and Mj are M whose brightness value (contour value) is M.
It is a feature point on the contour line (isoluminance line) of the group, and the pixel Ni, Nj, Nk is a feature point on the contour line (isoluminance line) of the N group whose luminance value (contour value) is N. Further, the pixels Oi, 0j, 0k are characteristic points on a contour line (contourance line) of the O group whose luminance value (contour value) is O, and have the above-mentioned contour values when the image is expanded. The data of the characteristic point group is stored in the reproduction side image memory. In the figure,
Each of the contour lines described above is indicated by a separate dotted line.

For any pixel other than the feature point, to find out which feature point the arbitrary pixel is close to,
For example, it can be performed as shown in FIG. FIG. 28
In the case where the pixels M and N of the characteristic points are present in the vicinity of the arbitrary pixel P in, the adjacent pixels are spirally inspected according to the path of the dotted arrow in the drawing from the arbitrary pixel P described above. , The pixel M of the feature point is reached before the pixel N of the feature point. As a result, the arbitrary pixel P is detected not as the pixel N of the characteristic point but as the pixel M near the characteristic point. Therefore, the pixel P is marked with a mark indicating that it is in the region of the pixel M of the characteristic point.

FIG. 29 shows a state in which the feature point symbols to which each arbitrary pixel belongs are written in a plurality of arbitrary pixels other than the pixel of the characteristic point according to the procedure described above with reference to FIG. Has been done. The dotted line connecting the above-mentioned feature point symbols is the boundary of the influence region of the above-mentioned feature points. now,
For example, focusing on Δ1, which is the boundary of three regions,
The pixels Nj, Nk, and Ok are adjacent to each other. Therefore, the pixels Nj, Nk, and Ok are regarded as the three feature points in the vicinity,
The triangles Nj, Nk, Ok are determined as the brightness interpolation plane, and the brightness values of the pixels existing inside the triangles Nj, Nk, Ok are applied by the brightness values of the brightness interpolation plane. Similarly, Δ2 which is the boundary of another three regions
Focusing on, the pixel Nj, Oj, Ok is adjacent to this Δ2. Therefore, the pixels Nj, Oj, Ok are close to each other.
Triangles Nj, Oj, Ok are determined as the luminance interpolation plane, and the triangles Nj, Oj, Oj,
The brightness value of the pixel existing inside Ok is allocated by the brightness value of the brightness interpolation plane described above.

By the procedure as described above, the pixel area affected by one feature point is searched for by the extension plane (extended solid in the case of a three-dimensional object), and the pixel area affected by the one feature point is searched. By detecting three feature points in the vicinity (4 feature points in the case of a three-dimensional object) from the boundary, the brightness function on the decompression side is determined from a small number of feature point information, and each brightness of untransmitted image information is determined. The value is applied by the above-mentioned interpolation value to reproduce the content of the entire image. It should be noted that circles, squares, rectangular parallelepipeds, rhombuses, etc. may be used as the extension surface in the case of a two-dimensional object, and spheres, spheroids, and bases are symmetrical as the extension solid in the case of a three-dimensional object. Two cones connected as planes, two pyramids connected as a plane of symmetry with the bottom surface, and the like may be used.

By the procedure described above, the brightness function on the decompression side is determined based on a small number of feature point information, and each brightness value in the untransmitted pixel information is interpolated by the brightness value on the brightness interpolation plane. The content of the entire image will be reproduced. As is clear from the above description, what is shared between the compression side and the decompression side is the brightness function of the screen, and if the position information of the feature points is expressed as a relative value for the entire screen, The number of pixels on the side does not have to match. That is, the characteristic information of the image extracted by the already proposed multidimensional image compression / expansion method is redrawn according to the number of pixels (resolution scale) on the expansion side.

FIG. 25 is a diagram showing a configuration example of the contour tracer 7 that can be used in the already proposed multidimensional image compression / expansion method. In the image memory 27 shown in FIG. 25, a predetermined number of pixels (for example, 512 pixels in the horizontal direction of the image, vertical direction of the image) of the video signal for each image by the analog-digital converter are provided in each of the horizontal and vertical directions of the image. A digital signal having a predetermined number of bits (for example, 8 bits) is stored for each pixel in a state of being decomposed into 480 pixels in the direction. Image memory 2
Reference numeral 7 denotes an image memory used for extracting contour lines of specific luminance in the image and performing an operation for determining a feature point. The output from the image memory 27 is supplied to the contour line tracer 7. The contour tracer 7
Then, the contour lines (contour lines) in the image information are extracted and the feature points are determined.

The contour line tracer 7 shown in FIG. 25 includes a plurality (n) of address generators 28 to 30, luminance determiners 31 to 33, luminance value generators 34 to 36, shift registers 37 to 39, respectively. Point determiners 40 to 42 and one alignment circuit 43 are provided. The above-mentioned address generators 28 to 30 generate address data for designating the address of the image memory 27, and apply the generated address data to the image memory 27.

The brightness value data read from the storage area of the address designated by the address data generated by the address generator 28 (29, ... 30) and the brightness value generating section 34 (35, ... 36). The brightness determining device 31 (32, ... 3) to which the specified specific brightness value data is given.
In 3), the above two data are compared and the comparison result is given to the address generator (28, ... 30). As a result, the address generator 28 generates new address data (including the middle of the pixel address) corresponding to M1 in FIG. 26B, for example (other address generators 29, ... 3).
It goes without saying that even with 0, address data is generated, respectively, and this is given to the image memory 27. In the image memory 27, the brightness value data read from the storage area of the address designated by the address data given as described above is supplied to the brightness determining unit 31 (32, ... 33) of the contour line tracer 7. .

In the brightness determiner 31 (32, ... 33), the brightness value data read from the image memory 27 and the specific brightness value data generated by the brightness value generating section 34 (35, ... 36) are stored. Is performed and the comparison result is given to the address generator (28, ... 30). Hereinafter, in the same manner, the above-described operation is sequentially performed, so that the brightness value substantially equal to the brightness value indicated by the specific brightness value data generated by the brightness value generation unit 34 (35, ... 36). Are sequentially generated. When each of the above address values indicates the middle of the pixel address values as in the example illustrated in FIG. 26, it is replaced with the neighboring pixel address values, and the above operation is sequentially performed. .

As described above, the address generator 28 (29,
The address data sequentially generated by the shift register 37 (38, ... 39) is also given to the shift register 37 (38, ... 39), and the parallel output of the shift register 37 (38, ... 39) is supplied. In the decision unit 40 (41, ... 42), one new address is input while the above-mentioned shift register 37 (38, ... 39) accumulates address data of a specific number of pixels (for example, 10 pixels). Each time one oldest address disappears, a pixel serving as a feature point is detected from the address group according to the above-described criterion for determining the feature point.
Then, the address value and the brightness value of the pixel serving as the characteristic point are supplied to the alignment circuit 43. In the alignment circuit 43, as described above, the address value and the brightness value of the feature point group indicating different contour values output from the plurality of feature point determiners 40, 41, ... An alignment operation is performed for sorting and sending. The output from the alignment circuit 43 is
It is sent as the output of the contour tracer 7. As the image memory 27, a multiport structure is used because the signal processing in the contour line tracer 7 traces a plurality of contour lines in parallel. Then, in terms of time, when scanning of one screen (one field period for an image in which an interlaced scanning method is adopted as a scanning standard) by the contour tracer 7 is completed, the characteristic points of the one screen are The extraction operation will end.

By the way, the isoluminance lines of the above-mentioned luminance information,
Alternatively, it is necessary to trace pixels with a specific luminance value when obtaining an equal-luminance surface of luminance information, but like the conventional general image contour tracing method, the center of boundary pixels is traced. In such a case, an error occurs in the contour between the original image and the image after reproduction, the processing time becomes long due to the large amount of processing, and the center of the boundary pixel is tracked. When a chain code code string is used, the center of one boundary pixel is made to correspond twice when a straight line having a width of one pixel is projected. Since there is a problem that the straight line remains one pixel width, the applicant company has proposed a contour tracking method for a binary image as disclosed in Japanese Unexamined Patent Publication No. 5-35872. did.

In the contour tracking method for a binary image disclosed in the above-mentioned Japanese Patent Laid-Open No. 5-35872, the tracking direction of the boundary point is defined by the black / white of four pixels around the boundary point of the pixel, and the tracking direction is defined. The tracking direction is determined so that there is a black pixel on the right side and a white pixel on the left side. When the tracking direction is upward, it is "1", when it is leftward, it is "2", when it is downward, it is "3", and it is In this case, the tracking direction in each case is assigned to each bit of the 4-bit tracking direction flag, the bit having the tracking direction is set to “1”, and the bit having no tracking direction is set to “0”. The tracking direction flag is attached to all boundary points, the boundary point is searched from the tracking direction flag, and the tracking is performed along the tracking direction from the starting point as a starting point. Change direction flag to line , All of the tracking direction flag is "0
The image is traced until it reaches "000" and the contour of the image is obtained.

In the above-described binary image contour tracking method, boundary pixels (boundary points) can be tracked by simply applying a predefined tracking direction to an input image, so that the tracking direction is searched every time. There is no need, a large amount of memory is not required, and the processing time is short, but the tracking direction is set so that there are black pixels on the right side and white pixels on the left side with respect to the tracking direction, and contour tracking follows the pixel boundary line. Since this is performed, a black pixel for one pixel appears on the left side in the tracking direction when the reproduced image is viewed. Although the above point does not cause any problem when the original image is, for example, a character, when the tracking target is a general image, the above point may cause deterioration in image quality. In the case of applying the contour tracking method of the binary image of (1) to the already proposed multidimensional image compression / expansion method described above, a solution thereof is needed.

In the already proposed multi-dimensional image compression / expansion method described above, isoluminous lines (or isoluminous surfaces) are approximated to polygons (or polygons), and when decompressing, polygonal approximation is performed by a straight line connecting feature points. (Or polygon approximation)) When determining the luminance information of pixels other than the feature points by the interpolation plane (or interpolation solid) determined by a plurality of neighboring feature points on the equal-luminance line (or the isoluminance surface) , The polygon-approximated isoluminance line (or isoluminance surface)
Is different from the original isoluminance line (or isoluminance surface) due to the compression of the information amount.
There is a case where the luminance order is reversed between them, and an abnormal state occurs in the luminance distribution in the reproduced image, which causes deterioration of the image quality. Therefore, a solution has been sought.

[0035]

SUMMARY OF THE INVENTION According to the present invention, the characteristic points of the image described above are obtained by finding characteristic points that meet specific conditions for isoluminance lines set for each predetermined specific luminance value in the luminance function of the image. In a multi-dimensional multi-valued image compression / expansion method that is used for transmitting, recording, and image restoration of the position of a point and a brightness value, a specific brightness boundary obtained by tracing the contour of a pixel having a specific brightness value during compression is constructed. At the center of each pixel
In the multidimensional multivalued image compression / expansion method in which the coordinates of the specific isoluminance line passing point are moved, and in the above-described multidimensional multivalued image compression / expansion method, in order to obtain an equiluminance line for each specific brightness value For each threshold value, a bright area having the equiluminance line as a boundary is filled with a bright symbol, and a dark area having the equiluminance line as a boundary is filled with a dark symbol to create a mask with a light-dark binary symbol. In the three-dimensional multi-valued image compression / expansion method and the above-mentioned multi-dimensional multi-valued image compression / expansion method, the above-described isoluminance lines are used as boundaries for each threshold value for obtaining the isoluminance lines for each specific luminance value during decompression. A bright area is filled with a bright symbol, and a dark area bounded by the isoluminance line is filled with a dark symbol to create a mask with a light-dark binary symbol, and the mask is arranged in the order of magnitude of luminance values according to a threshold value. Distribution And, the region between the adjacent mask,
After filling with the intermediate value of the brightness values by the threshold values of the two adjacent masks, the brightness value of each pixel has a relationship with the brightness values of the surrounding 8 pixels having each pixel as a central pixel as follows: (1) When the brightness value of the surrounding pixels is equal to the brightness value of the center pixel, the brightness value of the center pixel is undetermined,
(2) When the brightness value of the surrounding pixels is not higher than the brightness value of the central pixel, the brightness value of the central pixel is defined as "the intermediate value of the brightness values by the thresholds of both adjacent masks-a" (where a is a positive value). (3) When the luminance value of the surrounding pixels is not lower than the luminance value of the central pixel, the luminance value of the central pixel is set to “the intermediate value of the luminance values by the thresholds of the adjacent masks + a”. (4) If the relationship between the brightness values of the surrounding pixels and the brightness value of the central pixel is other than the above relationships (1) to (3),
It is the intermediate value of the brightness values by the thresholds of both adjacent masks,
It is determined according to which of the above conditions (1) to (4) is satisfied, the region center line is extracted for the brightness value undetermined region, and the pixel on the region center line is extracted. A multi-dimensional multi-value image compression / expansion method in which the brightness value is an intermediate value of the brightness values by the thresholds of both adjacent masks, and for the brightness value undetermined area as described above, the area center line is extracted and on the area center line described above. Regarding the brightness value of a pixel whose brightness value has not been determined after the brightness value of the pixel is set to the intermediate value of the brightness values by the threshold values of the adjacent masks, the known brightness at both extension line ends in the fixed direction of the pixel whose brightness value has not been determined. The brightness value is determined by the linear interpolation method using the brightness value and the distance of the pixel of
Alternatively, the above-described brightness value of the brightness value undetermined pixel is linearly interpolated by using the brightness value and the distance of the pixel of known brightness at both ends of the extended line of the straight line in each constant direction in each different direction of the pixel whose brightness value is undetermined. The surface interpolation value determined by the average value of the brightness values obtained by the method, or the brightness value of the remaining brightness value undetermined pixel is determined by using three pixels whose brightness values near the brightness value undetermined pixel are known. A multi-dimensional multi-valued image compression / expansion method is provided.

[0036]

Now, the multi-valued still image is compressed / expanded by taking as an example the case where the isoluminance plane showing a specific luminance value in the luminance function of the original image to be compressed is represented by FIG. A case will be described as an example. In FIG. 20, pixels surrounded by a dotted line are white pixels having a brightness value higher than that of the isoluminance surface, and pixels surrounded by a solid line and shaded are those of the isoluminance surface. It is said that the pixel is a black pixel having a lower brightness value than the brightness value. For the pixel group shown in FIG. 20 described above, a boundary line between white pixels and black pixels is applied by applying the binary image contour tracking method disclosed in Japanese Patent Laid-Open No. 5-35872. Upon tracking, the contour of the image as shown in Figure 21 is determined.

That is, the tracking of the above-mentioned boundary line is as follows.
When scanning is started from the upper left corner of the screen according to the raster scanning order and scanning is performed, the first boundary designated as the first boundary in FIG. 20 is found. When the tracking is started from the above point and the high-intensity surface is located on the left side of the tracking direction, the tracking start direction coincides with the horizontal scanning direction (CW ... clockwise), and the tracking start Either of the case where the direction coincides with the vertical scanning direction (CCW ... counterclockwise). In FIG. 21, a tracking direction type flag (CW, CCW) is attached to each tracking isoluminance line. As illustrated in FIG. 21 above, after the contour of the pixel is traced and obtained for each predetermined specific brightness value in the brightness function of the image, as illustrated in FIG. The specific isoluminance line passing point coordinates are moved to the center position of each pixel constituting the.

That is, the isoluminance lines when the tracking start direction coincides with the vertical scanning direction (CCW ... counterclockwise) are:
When the tracking start direction coincides with the horizontal scanning direction (CW ... clockwise), the isoluminance line is shifted to the pixel center position to the right in the tracking direction. As described above, when the reproduced image is obtained based on the specific luminance boundary obtained by tracing the contour of the pixel,
A black pixel for one pixel is generated on a specific side in the tracking direction to cause deterioration of image quality. As described above, each specific brightness boundary is obtained by tracking the contour of the pixel for each specific brightness value. This can be improved satisfactorily by moving the coordinates of the specific isoluminance line passing point to the center position of the pixel.

Next, the starting point is fixed, and the pixels on the isoluminance line are sequentially connected from the starting point by a virtual straight line, and the distance between the virtual straight line and the actual pixels existing between them is determined in advance. An actual pixel that exceeds the error allowable range E is registered as a feature point pixel. When the feature point pixel is found as described above, the feature point pixel is set as a new start point, the pixels on the isoluminance line are sequentially connected from the new start point by a virtual straight line, and the virtual straight line, An actual pixel whose distance to the actual pixel existing between them exceeds the predetermined error allowable range E is registered as a feature point pixel. In the following, successive feature points are found and registered with each successive feature point pixel as the next starting point. The neo-isoluminance line obtained by connecting the feature points sequentially obtained as described above is as shown in FIG.

By carrying out the above-mentioned work for each of the equal-luminance surfaces having different luminance values, the luminance function of the original image is degenerated into the data of the characteristic point group of the equal-luminance line, so that the image information Compression will be performed. The positions and brightness values of the characteristic points of the image described above are used for transmission, recording, image restoration, etc. as the original image information that is highly efficient compressed, and the positions and brightness values of the characteristic points of the image described above. Based on and, on the decompression side, isoluminance lines can be easily drawn and restored. The important point here is that the isoluminance lines restored on the decompression side are drawn by the end point (feature point) designating vector, so the pixel density of the image memory on the decompression side is set on the compression side. Even if the pixel densities of the image memories are different, the shape of the isoluminance lines restored on the decompression side is hardly influenced by the above-mentioned physical conditions.

As described above, the information which is highly efficiently compressed into the information of the position of the characteristic point of the image and the luminance value which meets the specific condition obtained for each specific isoluminance line is expanded to obtain the reproduced image. At that time, for each threshold value for obtaining an isoluminance line for each specific luminance value,
A bright region having the equiluminance line as a boundary is filled with a bright symbol, and a dark region having the equiluminance line as a boundary is filled with a dark symbol to create a mask of light and dark binary symbols. FIG. 24 is a mask created by filling the pixels on the decompression side where the isoluminance line at a certain luminance value has passed and the area on the right side (low luminance side) in the tracking direction.

As described above, light and darkness 2 is defined with isoluminance lines as boundaries.
By creating a mask with a value symbol, an isoluminance line (or isoluminance surface) is approximated to a polygon (or polygon),
An isoluminance line (or isoluminance surface) that has been polygon-approximated (or polyhedron-approximated) by a straight line connecting feature points during expansion
In the case where the luminance information of pixels other than the feature points is determined by the interpolation plane (or interpolation solid) determined by a plurality of feature points in the vicinity of
There is no inversion of the luminance order between
It does not cause an abnormal state in the luminance distribution in the image to deteriorate the image quality.

In FIG. 12, when the gradation of the luminance of the image is 256 (000 to 255) by the 8-bit digital luminance signal, as shown in FIG. 9 shows an example in which nine kinds of masks that make the above-described 256 gradations of brightness into nine kinds of brightness gradations are configured by the first to eighth thresholds having different brightness values as thresholds. Further, FIG. 6 shows an example of a case where a mask having a mask number corresponding to the mask number shown in FIG. 12B is created for the original image whose luminance gradation is 256. . In FIG. 6, the screen displayed as mask 1 is entirely white, but as shown in (b) of FIG. 12, the mask 1 has a threshold value of 25.
A luminance value corresponding to 30 in 6 gradations is set, and a portion where the luminance value of the image is higher than the threshold value is painted white, and a portion where the luminance value of the image is lower than the threshold value is painted black. Since the mask in the opened state is created, the whole screen displayed as mask 1 in FIG. 6 is shown in white, which means that there are 256 gradations in the image to be compressed. It means that there is no portion lower than the luminance value corresponding to 30 of No.

The screen displayed as the mask 8 in FIG. 6 is entirely black, but FIG.
As shown therein, the mask 8 has a threshold value set to a luminance value corresponding to 240 in 256 gradations, and a portion where the luminance value of the image is higher than the threshold value is painted white, and Since a mask in which the portion of the image whose luminance value is lower than the threshold value is filled with black is created, FIG.
The entire screen displayed as the inner mask 8 is shown in black, which means that the image to be compressed has a portion higher than the luminance value corresponding to 240 in 256 gradations. It means not to. In addition, the screen labeled Masks 2-7 in FIG. 6 is partially black in the drawing, which is less than the thresholds used to create Masks 2-7. It means that the high luminance value and the low luminance value are mixed in the image to be compressed.

Then, when a plurality of masks displayed with respective mask numbers shown in FIG. 12B and FIG. 6 are overlapped, an image having a brightness of 9 gradations is reproduced. Now, in each mask displayed with each mask number shown in (b) of FIG. 12 and FIG. 6, the luminance value of the white-painted portion is represented by the numerical value of each mask number. By the way, FIG. 7 shows the luminance distribution of an image obtained in a state in which a plurality of masks indicated by mask numbers 1 to 8 in FIG. 6 are superposed by the distribution of numerical values.

In FIG. 12B, the brightness of 256 gradations represented by the 8-bit digital brightness signal is compressed into brightness values corresponding to the respective threshold values defined by the mask number 0 to the mask number 8. Is in a closed state. In general, assuming that the mask group is n masks, mask number 0 → pixel of luminance value 0 to first equal luminance value mask number 1 → first equal luminance value to second equal luminance value Pixel of mask number 2 → Pixel of second equal luminance value to third equal luminance value Mask number of 3 → Pixel of third equal luminance value to fourth equal luminance value :::::: Mask number i → third Pixels of i equal luminance value to i + 1th equal luminance value ::::::: mask number n → nth equal luminance value to 255th pixel. That is, if n masks are created as described above, the brightness value of each pixel distributed from brightness 0 to brightness 255 is classified into n + 1 categories. The above-mentioned twelfth example (b) is an example when n = 8.

When the brightness of the pixels included in each of the above-mentioned categories is represented by the intermediate representative value of the brightness range, 9-level equal brightness lines are reproduced in the above-mentioned 12th (b) and the example of FIG. Will be done. Next, among the plurality of equal-intensity lines, three neighboring pixels are selected from two adjacent equal-intensity lines, and the above-mentioned 2
By interpolating the brightness between two equal brightness lines, a one-dimensional display can be obtained, for example, as shown in FIG. 11 (a). Now, even if the original image has 256 gradations, it is assumed that the image expansion is performed by interpolation in a state where the luminance gradations are degenerated such as 9 luminance levels in the above example. , The quality of the reproduced image is not sufficient.

Therefore, in order to improve the quality of the image to be reproduced, in the interpolation reproduction of the brightness value, the brightness value of the interpolation end point is not set to the intermediate value of the simple category as described above. The masks are arranged in the order of the brightness value according to the threshold value, and the area between the adjacent masks is filled with the intermediate value of the brightness values according to the threshold values of the adjacent masks, and then the brightness value of each pixel is The relationship with the brightness values of the surrounding eight pixels, each of which is the center pixel, is (1) When the brightness value of the surrounding pixels is equal to the brightness value of the center pixel, the brightness value of the center pixel is undetermined. , (2) When the brightness value of the surrounding pixels is not higher than the brightness value of the central pixel,
The brightness value of the central pixel is defined as "the intermediate value of brightness values by the thresholds of both adjacent masks-a" (where a is a positive value).
(3) When the brightness value of the surrounding pixels is not lower than the brightness value of the central pixel, the brightness value of the central pixel is set to “the intermediate value of the brightness values by the thresholds of both adjacent masks + a”. When the relationship between the brightness value of the pixel and the brightness value of the central pixel is other than the above relationships (1) to (3), the brightness value is set to an intermediate value between the brightness values according to the threshold values of the adjacent masks. The quality of the reproduced image can be improved by making a determination according to which of the conditions (1) to (4) is satisfied.

A specific example of the case where the relationship between the central pixel and the luminance values of the eight surrounding pixels is (1) to (4) described above is surrounded by four dotted line frames shown in FIG. Each of the four dotted line frames shown in FIG. 7 is shown in FIG. 8 for easy understanding. By the way, if the relationship between the central pixel and the luminance values of the eight surrounding pixels is (1),
That is, when the brightness value of the surrounding pixels is equal to the brightness value of the center pixel, the brightness value of the center pixel is undetermined. An example of the case is 9 in the dotted line frame shown at the leftmost end in FIG.
The brightness value of the nine pixels is the same numerical value 4. In this case, the brightness value of the central pixel is “undefined”, and in the drawings after FIG. 9, for simplicity of illustration, “undefined” is indicated by the symbol “•”.

When the relationship between the central pixel and the luminance values of the eight pixels surrounding the central pixel is (2) described above, that is, when the luminance values of the peripheral pixels are not higher than the luminance value of the central pixel, the central pixel is 8 is set to be the “intermediate value −a of the brightness values by the threshold values of both adjacent masks” (where a is a positive value), the example of the case is the dotted line shown second from the left in FIG. Although it is shown by nine pixels in the frame, the brightness value of the center pixel in such a case is “low”, and the brightness of the center pixel is shown in the drawings after FIG. 9 for simplification of the drawing. Will indicate the "low" state using the "-" symbol.

Further, when the relationship between the central pixel and the luminance values of the eight surrounding pixels is (3) described above, that is, when the luminance values of the surrounding pixels are not lower than the luminance value of the central pixel, An example of the case where the brightness value of a pixel is “the intermediate value of brightness values by the thresholds of both adjacent masks + a” is shown in FIG.
In FIG. 9, the luminance value of the central pixel is “high”, which is shown by nine pixels in the dotted line frame third from the left in FIG. For the sake of simplicity, the state in which the brightness of the central pixel is “high” is shown by using a “+” symbol.

Furthermore, the relationship between the center pixel and the brightness values of the eight pixels around it is the above-mentioned case (4), that is, the relationship between the brightness values of the surrounding pixels and the brightness value of the center pixel is the above. In cases other than the relationships (1) to (3), the intermediate value of the brightness values by the threshold values of the adjacent masks is used. An example of the case is 9 in the dotted line frame shown at the right end in FIG. Although the brightness value of the central pixel in such a case is shown as “intermediate” in this case, the brightness of the central pixel is “intermediate” for simplification of the drawing.
The state of is indicated by using the symbol "=". FIG. 9 illustrates the relationship between the luminance values of the pixels shown in FIG. 7 using the symbols “•”, “−”, “+”, and “=” described above, and FIG. In a) to (l), the luminance values are three-dimensionally shown in the height direction so that the relationship between the central pixel and the luminance values of the eight surrounding pixels and the way of using the symbols described above can be clearly understood. FIG.

Next, for the brightness value indeterminate region, a region center line (skeleton), that is, a group of points equidistant from the end of the region is extracted, and the brightness values of the pixels on the region center line are adjacent to each other in both masks. It is an intermediate value of the brightness values according to the threshold value of.
13 to 16 are views for explaining the above process. FIG. 13 shows the luminance value before correction of only the indefinite area indicated by the symbol “•” in FIG. 9, and FIG. 14 omits the above-mentioned luminance value, and only the indefinite area has an asterisk “*”. 15 is a diagram showing a state in which pixels on the center line of the indefinite region are given an intermediate mark = and an intermediate luminance value, and FIG. 16 shows all the marks given according to the above-mentioned promise. It is a figure which is using and has shown the brightness value of each pixel.

By the way, the relationship of the brightness values in the case where the brightness value of the pixel is "intermediate level", "intermediate brightness-", and "intermediate brightness +" is shown in FIG. In FIG. 12A, the difference between the threshold values of the adjacent masks described above, that is, the difference between the i-th threshold value and the i + 1-th threshold value is shown as d. The intermediate level shown in FIG. 12A is an intermediate brightness value between the brightness values determined by the threshold values of the adjacent masks, and FIG. The brightness level of the low level "intermediate brightness-" shown in the inside is set to be a brightness level lower than the above-mentioned intermediate level by d / 3, and further, the high level shown in (a) of FIG. The brightness level of the level “intermediate brightness +” is a brightness level higher by d / 3 than the above-mentioned intermediate level. And Figure 1
To the right of 2 (b), for each mask number,
Intermediate level, low level, high level values, display symbols, etc. are shown.

FIG. 17 shows the luminance value of each pixel shown using the intermediate level, low level, and high level values for each mask number shown in FIG. 12B. In FIG. 17, the brightness value of the pixel is still “undefined”, and the pixel indicated by the undefined mark “·” exists. As described above, FIG. 19 shows the brightness values of the pixels whose brightness value is indeterminate after the brightness value of the pixel on the area center line is set to the intermediate value of the brightness values by the threshold values of the adjacent masks. As described above, the luminance value and the distance (L1, L2, or L3, L3, L3, L3, L3, L3, L3, L3, L3, L3
L4) is used to determine the brightness value by a linear interpolation method, or the brightness value of the brightness value undetermined pixel described above is determined by the extension of both ends of a straight line in each direction in different directions of the brightness value undetermined pixel. Is determined by the average value of the brightness values obtained by the linear interpolation method using the brightness value and the distance of the pixel having the known brightness, or the brightness value of the remaining brightness value undetermined pixel is set to the brightness value undetermined pixel It is determined by the surface interpolation value performed using three pixels whose luminance values in the vicinity of are known. As a result, a reproduced image as illustrated in FIG. 18 in which the luminance values of all pixels are determined can be obtained.

[0056]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Specific contents relating to the multidimensional multivalued image compression / expansion method of the present invention will be described in detail below with reference to the accompanying drawings. FIG. 1 is a block diagram of the compression side in the multidimensional multivalued image compression / expansion system of the present invention, and FIGS. 2 to 4 are signals provided on the compression side in the multidimensional multivalued image compression / expansion system shown in FIG. FIG. 5 is a block diagram of the components of the processing unit, FIG. 5 is a block diagram on the decompression side in the multidimensional multivalued image compression / expansion method of the present invention, and FIGS. 6 to 24 and FIGS. 26 to 29 are multidimensional multivalued image compression / expansion. FIG. 25 is a block diagram showing a configuration example of a contour tracer used for explaining the method. In FIG. 1 showing a configuration example on the compression side in the multidimensional multivalued image compression / expansion system of the present invention, reference numeral 1 is a signal source of an image signal to be subjected to multidimensional multivalued image compression / expansion.

The image signal source 1 is, for example, an image pickup device (TV camera) or a VTR which generates an image signal,
Others can be used. Further, 2 is an analog-digital conversion unit, 3 is a color memory, 4-1, 4-2, ... 4-n
Is a signal processing unit. The specific configuration of each of the signal processing units 4-1, 4-2, ... 4-n is, as illustrated in the signal processing unit 4-1, a predetermined brightness level information extracting unit 5 ( A specific configuration example of the extraction unit 5 of the predetermined brightness level information is shown in FIG. 2), a binary memory 6, and a contour line tracer 7 (a specific configuration example of the contour line tracer 7 is shown in FIG. 3). )), A contour line address list 8 and a polygonal approximate address list 9 (a specific configuration example of the polygonal approximate address list 9 is shown in FIG. 4). Reference numeral 10 is a multiplexer, 11 is an encoder and transmitter, and 12 is a transmission line (or recording medium).

Further, in FIG. 5 showing an example of the configuration on the decompression side in the multidimensional multivalued image compression / decompression system of the present invention,
Reference numeral 12 is a transmission line (or recording medium) 12 shown in the compression side in the multidimensional multivalued image compression / expansion system of the present invention shown in FIG. The image information in a highly efficient compressed state via the transmission line (or recording medium) 12 is given to the reception decoder 13. Reference numerals 14-1, 14-2 ... 14-n are signal processing circuits having the same configuration mode, and a specific configuration example thereof is the signal processing circuit 14.
It is shown in -1. In the signal processing circuit 14-1, 15 and 16 are end point address registers, 17 is a local image memory, 18 is a polygonal interpolation mask generator, 19 is a multi-value determination operator, 20 is a skeleton brightness determiner, and 21 is a brightness interpolation plane. It is an arithmetic unit. Also, in FIG.
3 is an image memory, 25 is a video signal generator, and 26 is a monitor receiver.

In the configuration on the compression side in the multi-dimensional multi-valued image compression / expansion system of the present invention shown in FIG. It is generated and supplied to the analog-digital conversion unit 2. The image signal source 1 may have any configuration as long as it is a video signal generating device capable of generating image information to be compressed / expanded by the multidimensional multivalued image compression / expansion method of the present invention. Can also be used. The image signal source 1 shown in FIG.
It is said to have a structure capable of generating a primary color signal.
Then, the three primary color signals generated from the image signal source 1 are supplied to the analog-digital conversion unit 2.

In the analog-to-digital conversion section 2, the luminance signal for each image obtained from the three primary color signals supplied thereto has a predetermined number of pixels (for example, the horizontal direction of the image) for each horizontal and vertical direction of the image. Direction, 512 pixels in the vertical direction, and 480 pixels in the vertical direction of the image), and generates and outputs a digital luminance signal Y of a predetermined number of bits (for example, 8 bits) for each pixel in the decomposed state. Is supplied to each of the signal processing units 4-1, 4-2, ... 4-n. As for the chroma signal, a digital color difference signal corresponding to the pixel is generated and supplied to the color memory 3.

An example of a concrete configuration of each of the signal processing units 4-1, 4-2 ... 4-n to which the digital luminance signal Y is supplied is shown in a frame of a chain line of the signal processing unit 4-1. However, in the predetermined brightness level information extraction unit 5 provided in each of the signal processing units 4-1, 4-2, ... 4-n, each signal processing unit 4-1, 4-2 ,. For each 4-n, the image information to be compressed is binarized and output with different brightness thresholds that are predetermined, and the pixel address is also output. Each of the signal processing units 4-1, 4-2 ... 4 described above
2 shows an example of the configuration of the predetermined brightness level information extraction unit 5 provided in the circuit n. In FIG. 2, the input terminal 5a is supplied with the digital brightness signal Y from the analog-digital conversion unit 2. Further, a clock signal is supplied to the input terminal 5b from a control device (not shown).

That is, the digital brightness signal Y supplied to the extraction unit 5 of the predetermined brightness level information is compared in the comparator (magnitude comparator) 51 with the specific brightness threshold supplied from the brightness threshold setting unit 52. hand,
The binarized output of the digital luminance signal Y is sent from the comparator 51 to the output terminal 5c. The brightness threshold setting unit 52 described above
, A predetermined brightness threshold value is set in binary by a ROM, a DIP switch, a fuse array, or the like. The brightness threshold value set in the brightness threshold value setting unit 52 in the predetermined brightness level information extracting unit 5 provided in each of the signal processing units 4-1, 4-2 ... 4-n is, for example, (b) of FIG. Like the first threshold value to the eighth threshold value illustrated therein, the brightness value is a predetermined brightness value when the multi-dimensional multi-value image compression / expansion method is performed. The comparator 51 sends a binary output of the comparison result at the moment when the clock signal is given to the output terminal 5c.

Each of the signal processing units 4-1, 4-2, ...
The binarized output of the digital luminance signal output from each predetermined luminance level information extraction unit 5 in 4-n is
It is stored (stored) in the binary memory 6 provided in each of the signal processing units 4-1, 4-2, ... 4-n. The binarized output of the digital luminance signal stored in the binary memory 6 is the address designated by the binary memory address output from the address counter 72 (see FIG. 3) provided in the contour tracer 7. Is read out and supplied to the determiner 71 (see FIG. 3) of the contour line tracer 7.

Now, the binarized outputs of the digital brightness signals output from the respective predetermined brightness level information extraction units 5 in the signal processing units 4-1, 4-2, ... The binarized signal in the state binarized at a specific luminance threshold value, for example, the state illustrated in FIG. 20, and the binarized signal read from the binary memory 6 is
In the discriminator 71 (see FIG. 3) provided in the contour line tracer 7, first, for the binarized pixel group as shown in FIG. 20 described above, from the upper left corner of the screen according to the raster scanning order. When scanning is started, scanning is performed, and when the first boundary is found, tracking of the contour of the pixel with a specific brightness value is started from that point as the starting point, and the high brightness surface is located on the left side of the tracking direction. When the tracking start direction coincides with the horizontal scanning direction (CW ... clockwise),
When the tracking start direction matches the vertical scanning direction (CCW ...
Counterclockwise), the contour of the pixel is traced and an output signal (address strobe) of contour line information is sent to the output terminal 7c (see FIG. 3).

The information H and V of the step history (change in position in the horizontal scanning direction, change in position in the vertical scanning direction) in tracing the contour of the pixel having the specific luminance value described above is supplied to the address counter via the multiplexer 73. Supply to 72. As a result, the address counter 72 sequentially outputs the tracking address sequence as a binary memory address output to the output terminal 7b (see FIG. 3) according to the step history, and
The contour line address is output to the output terminal 7d (see FIG. 3). An output signal (address strobe) of contour line information output from each contour line tracer 7 in each of the signal processing units 4-1, 4-2, ... 4-n and a contour line address output are supplied. In Listing 8, after storing the contour address output above,
For example, as illustrated in FIG. 22, the specific isoluminance line passing point coordinates are moved to the center position of each pixel forming the specific luminance boundary.

Each of the signal processing units 4-1, 4-2, ...
The address output of the center position of each pixel constituting the specific luminance boundary output from each contour line address list 8 in 4-n is output in each of the signal processing units 4-1, 4-2 ,. It is supplied to the rectangular approximate address list 9. In FIG. 4 showing a specific configuration example of the polygonal approximate address list 9, the address information of the center position of each pixel forming the specific luminance boundary output from the contour line address list 8 is input terminal 9a. Is entered. Then, the address information of the center position of each pixel forming the specific luminance boundary, which is supplied to the input terminal 9 a of the polygonal approximate address list 9, is supplied to the end point address register 91 and the shift register 93. The output of the above-mentioned end point address register 91 is supplied to the interpolation address calculator 92.
The address information of the first storage section in the shift register 93 is also given.

In the interpolation address calculator 92, the horizontal scanning direction of the image is changed to the Xh axis and the vertical scanning direction in order to replace the distances between the feature points and the interpolation line described above with simple values for comparison. When the Yv axis is used, each of the feature points described above and the Xh axis in the horizontal scanning direction (or the Yv axis in the vertical scanning direction)
An address for comparing the address value of the Yv-axis in the vertical scanning direction (or the address value of the Xh-axis in the horizontal scanning direction) on the interpolation straight line at the address is calculated. The switching of the corresponding axes is performed at the intersection angle between the interpolation straight line and the Xh axis in the horizontal scanning direction, and the threshold value is set to 45 degrees on the assumption that one pixel is a square. That is, when the absolute value of the intersection angle between the interpolation line and the Xh axis in the horizontal scanning direction is 45 degrees or less (or other value), the first accumulation section in the shift register 93 is sequentially processed. The interpolation address group at the position where the contour line address information that is input and sequentially held for the sequential accumulation sections in the shift register 93 corresponds to the horizontal scanning direction Xh axis (or vertical scanning direction Yv axis) address The address value calculated by the end point address and the sequential address information in the first accumulation section in the shift register 93) is supplied to the register 94 as an interpolation address.

Then, the sequential contour line pixel addresses sequentially stored in the shift register 93 and the register 9 are stored.
The interpolation addresses sequentially stored in 4 are those corresponding to each other as shown in FIG.
It is supplied to C3 ... Cn. Each comparative extractor C described above
2, C3, ... It is given to the register 95 and the address value of the feature point is stored in the feature point address register 95. At the same time, the address value of the characteristic point is given to the above-mentioned end point address register 91 as a new end point address value.

At the input terminal 9a in the polygonal approximate address list 9 illustrated in FIG. 4, the address information of the center position of each pixel constituting the specific luminance boundary supplied from the contour line address list 8 is the tracking start point address. Assuming that the operation in the polygon approximate address list 9 is information, the above-mentioned tracking start point address information is stored in the end point address register 91 and at the same time stored in the first accumulation section 1 of the shift register 93. Remembered. Since the polygonal approximate address list 9 is supplied with the sequential contour line address group output from the contour line address list 8 described above, in each of the storage sections 1, 2, 3 ... N of the shift register 93. The memory contents shift one after another.

However, the above-mentioned end point address register 9
Since the storage content of No. 1 has not changed yet, the storage of the first storage section 1 in the shift register 93 supplied from the first storage section 1 in the shift register 93 to the interpolation address calculator 92. The linear interpolation value address group whose contents are updated is output. As described above, every time a group of linear interpolation value address groups is output, the accumulation sections 1, 2, ... N in the shift register 93 and horizontal (or vertical) are taken into consideration while considering the inclination of the straight line. The interpolation value address group corresponding to the direction address is output to the storage sections 2, 3, 4, ... N of the register 94.

.. n in the shift register 93 and the accumulation sections 2, 3 in the register 94.
.. Cn provided separately from the comparison extractors C2, C3, ...
..N for the shift register 93 and two input information individually supplied from the accumulation sections 2, 3, 4 ... n of the register 94 for 2, C3 ... Cn. The absolute value of the difference (corresponding to the distance between the contour line and the interpolation line on the screen) is set as a feature point in the state where the contour line address in a state where it exceeds a predetermined threshold value is set in the feature point address register 95. Store.

A large number of the comparison extractors C2, C2, C3 described above.
If a plurality of comparison / extractors in Cn simultaneously output characteristic point information, the contour line address on the side close to the address value stored in the end point address register 91 is adopted as a new end point address. Then, the address value is stored in the feature point address register 95, and the new end point address is stored in the end point address register 91. Even if a plurality of feature point addresses disappear in the above case, it is not necessary to restore them as feature point addresses.

Each signal processing section 4-1 shown in FIG.
The feature point address group for each different brightness threshold individually output from 4-2 ... 4-n is given to the encoding unit and the transmission unit 11 via the multiplexer 10. A chroma signal component is also supplied to the color memory 3 from the color memory 3 via the multiplexer 10. In the encoding unit and the transmission unit 11, for example, a known signal such as Huffman encoding is applied to the signal supplied thereto. High-efficiency encoding is performed and transmitted (or recorded) to the receiving side (or reproducing side) via the transmission line (or recording medium) 12.

In the embodiments described so far, the detection of the feature point address group for each different brightness threshold value is performed from the already detected feature point pixel to the contour line {in the case of three-dimensional brightness information, the contour surface is used. }, It is determined that a pixel which is a pixel between two pixels described above and which has a distance exceeding a certain threshold distance with respect to a virtual straight line with a pixel traced in a certain direction is a feature point. However, in the implementation of the present invention, the detection of the feature point address group for each different brightness threshold value is carried out by isoluminance lines (contour lines) of the luminance function (of three-dimensional luminance information). In this case, the pixels of the positive and negative maximum points of curvature of the isoluminance surface} or the curve of the contour line {contour surface in the case of three-dimensional luminance information} exceeds a predetermined threshold angle. If the pixel in the case is determined to be a feature point, the feature point is determined. May be in, it may be contour tracer 7 configuration aspects already described for FIG. 25 is used as a contour tracer 7.

Next, with reference to the block diagram on the decompression side in the multidimensional multi-valued image compression / decompression method of the present invention, the case of decompressing and restoring the luminance function of the original image will be described. Figure 5
In the reception decoder 13 in, the high-efficiency coded signal supplied thereto is decoded by the transmission line (or recording medium) 12, and the decoded signal is supplied to the signal processing circuits 14-1, 14-2 ... 14-n. give. A large number of signal processing circuits 14-1, 14-2, ... 14-n provided on the extension side are shown in FIG.
A large number of signal processing units 4 provided on the compression side in the multidimensional multivalued image compression / expansion method of the present invention described above with reference to FIG.
-1, 4-2, ... 4-n provided corresponding to each of the signal processing circuits 14-1, 14-2,
... 14-n are used for the image processing of the image signal binarized by using different specific brightness threshold values. A concrete configuration example of the above-mentioned many signal processing circuits 14-1, 14-2, ... 14-n is shown in the signal processing circuit 14-1.

In the reception / decoding device 13 described above, a large number of signal processing units 4-1, 4-2, ... 4 provided on the compression side in the multidimensional multi-valued image compression / expansion system of the present invention described above.
-N, among the high-efficiency coded signals compressed for the image signals binarized by using different specific luminance thresholds, the high level of the image signal binarized by using the specific luminance thresholds is used. The efficiency coded signals are distributed and supplied to the corresponding signal processing circuits 14-1, 14-2, ... 14-n. Each of the signal processing circuits 14-1 and 1 described above
4-2, ... 14-n, the image signal binarized using different specific luminance threshold values is binarized using the specific luminance threshold value of the high-efficiency coded signal compressed. Although signal processing is performed on a high-efficiency coded signal of an image signal, the signal processing operation performed in each of the signal processing circuits 14-1, 14-2, ... In the description, the signal processing circuit 14-1 will be specifically described.

When the characteristic point addresses sequentially supplied from the reception decoder 13 to the signal processing circuit 14-1 are stored in the end point address register 15 and the end point address register 16, the end point address register 15 and the end point address are stored. The feature point address is supplied from the address register 16 to the polygonal interpolation mask generator 18 as both end point addresses. The polygonal interpolation mask generator 18 calculates the addresses of the linear interpolation pixels of the two end points given to the polygonal interpolation mask generator 18 and writes the address values in the multi-port local image memory 17 at the designated brightness.

Next, when a new feature point address is supplied from the reception decoder 13 to the signal processing circuit 14-1, the new feature point address is stored in the end point address register 15 as a new end point address and The end point address previously stored in the end point address register 15 is moved to and stored in the end point address register 16. Then, the polygonal interpolation mask generator 18 calculates the addresses of the linear interpolation pixels of the two end points given to the polygonal interpolation mask generator 18, and writes the address value in the local image memory 17 of the multiport at the specified brightness. The polygonal interpolation mask generator 18 performs the above-described operation every time a new feature point address is supplied from the reception decoder 13 to the signal processing circuit 14-1, and a new interpolation line is generated one after another. Is calculated and the sequential addresses are written in the local image memory 17 at the designated brightness.

When the closed curve is completed by the interpolation line, the polygonal interpolation mask generator 18 applies the inside of the closed curve in the local image memory 17 with the specified brightness to obtain the mask of the specific brightness level. To generate. In this way, for each threshold value for obtaining the isoluminance line for each specific luminance value, the bright region bounded by the isoluminance line is filled with a bright symbol, and the dark region bounded by the equiluminance line is defined. An area can be filled with a dark symbol to create a mask with a light-dark binary symbol. In each of the signal processing circuits 14-1, 14-2, ... 14-n described above, a high-efficiency coded signal compressed for a binarized image signal using different specific luminance thresholds is specified. Since the signal processing is performed on the high-efficiency coded signal of the binarized image signal using various brightness thresholds, each of the signal processing circuits 1 described above is used.
By the signal processing operation performed at 4-1, 14-2, ... 14-n, the bright regions bounded by the equal-intensity lines for each different specific luminance value are filled with bright symbols, and the above-mentioned equal-intensity lines are It is possible to generate a plurality of masks as illustrated in FIG. 6 in which a dark region as a boundary is filled with a dark symbol.

After the above-mentioned work in the polygonal interpolation mask generator 18 is completed, the multi-value determination operator 19 and the skeleton brightness determiner 20 cause the local image memory 1 to operate.
It operates so as to change the luminance plane of No. 7 so as to have multi-level luminance. That is, as described above, in order to improve the quality of the image to be reproduced, the brightness value of the interpolation end point is not set to the intermediate value of the simple category as described above in the interpolation reproduction of the brightness value. , The masks are arranged in the order of the magnitude of the brightness value by the threshold value, and the area between the adjacent masks is
After painting with the intermediate value of the brightness values by the threshold values of the adjacent masks, the brightness value of each pixel has a relationship with the brightness values of the surrounding 8 pixels with each pixel as the center pixel, (1) When the brightness value of the surrounding pixels is equal to the brightness value of the central pixel, the brightness value of the central pixel is undetermined. (2) When the brightness value of the surrounding pixels is not higher than the brightness value of the central pixel, the brightness value of the central pixel is set to (the intermediate value of the brightness values by the threshold values of the adjacent masks-a) (where a is a positive value). Value). (3) When the brightness value of the surrounding pixels is not lower than the brightness value of the central pixel, the brightness value of the central pixel is set to (the intermediate value of the brightness values by the thresholds of both adjacent masks + a). (4) When the relationship between the brightness values of the surrounding pixels and the brightness value of the central pixel is other than the above relationships (1) to (3), an intermediate value of the brightness values according to the threshold values of both adjacent masks is used. To do. Therefore, the quality of the reproduced image can be improved by making a determination depending on which of the conditions (1) to (4) described above is satisfied.

Further, regarding the brightness value indeterminate region, a region center line (skeleton), that is, a group of points equidistant from the end of the region is extracted, and the brightness value of the pixel on the region center line is extracted between the adjacent masks. The skeleton brightness determiner 20 is set to have an intermediate value of the brightness values according to the threshold value (see FIGS. 13 to 16).
Operates to write the determined brightness value in the local image memory 17 described above. When the above-described brightness determination work by the multi-value determination operator 19 and the skeleton brightness determiner 20 is completed, the brightness interpolation surface calculator 21 sets the brightness value of the brightness undetermined pixel to, for example, “(a) in FIG. Intermediate level ",
The brightness value is determined to have a relationship of brightness values as shown by “intermediate brightness −” and “intermediate brightness +”, or the brightness value of the pixel on the area center line is determined by the threshold value of both adjacent masks. With respect to the brightness value of the remaining brightness value indeterminate pixel after the intermediate value is set, as shown in FIG. 19, pixels of known brightness values at both ends of the extension lines of the above-described brightness value indeterminate pixel px in a certain direction. The brightness value of (p1, p2, or p3, p4) and the distance (L1, L2, or L3, L4) are used to determine the brightness value by a linear interpolation method, or the brightness of the brightness-undetermined pixel described above. The average value of the brightness values obtained by the linear interpolation method by using the brightness value and the distance of the pixels of known brightness at both ends of the straight line in each constant direction in each different direction of the pixels whose brightness value is undetermined Or the remaining brightness value The brightness value of the undetermined pixel is determined by the surface interpolation value performed by using three pixels whose brightness value in the vicinity of the pixel whose brightness value is undetermined is known.

Each signal processing circuit 14-1, 14-2, ... 1
The image signals decompressed by signal processing at 4-n are stored in the image memories 22 and 23. The two image memories 22 and 23 described above operate by alternately repeating the writing operation and the reading operation. The image signals read from the image memories 22 and 23 are processed by a video signal generator 24 as video signals according to a television system of a specific scanning standard, and the monitor receiver 2
5, the reproduced image is displayed on the display surface of the monitor receiver.

[0083]

As is apparent from the above detailed description, the multidimensional multivalued image compression / expansion method of the present invention is
The specific isoluminance line passing point coordinate is moved to the center position of each pixel forming the specific luminance boundary obtained by tracing the contour of the pixel for each predetermined specific luminance value in the luminance function of the image,
A characteristic point that meets a specific condition for the specific isoluminance line is obtained, and the position and the luminance value of the characteristic point of the image are transmitted, recorded, image restored, etc. as information in which the original image information is highly efficiently compressed. Therefore, when a reproduced image is obtained based on a specific luminance boundary obtained by tracing the contour of a pixel, a black pixel for one pixel is generated on a specific side in the tracing direction, and the image quality is improved. The point causing the deterioration of is to move the specific isoluminance line passing point coordinates to the center position of each pixel forming the specific luminance boundary obtained by tracing the contour of the pixel for each specific luminance value in the present invention. By doing so, it is possible to improve satisfactorily, and the information highly efficient compressed to the information of the position and the brightness value of the characteristic point of the image that meets the specific condition obtained for each specific isoluminance line,
When obtaining a reproduced image by expanding, for each threshold value for obtaining the isoluminance line for each specific luminance value, the bright area bounded by the isoluminance line is filled with a bright symbol, and the isoluminance line is defined. Fill the dark area bounded by with the dark symbol and light and dark 2
Create a mask with a value symbol, approximate an isoluminance line (or isoluminance surface) to a polygon (or polyhedron), and approximate the polygon to a polygon (or a polyhedron approximation) with a straight line connecting feature points when expanding. Even when the brightness information of pixels other than the feature points is determined by the interpolation surface (or interpolation solid) determined by a plurality of neighboring feature points on the line (or the isoluminance surface), 2) does not cause the reversal of the luminance order, and therefore does not cause an abnormal state in the luminance distribution in the image to cause the deterioration of the image quality. Are arranged in the order of the size, and the area between adjacent masks is filled with an intermediate value of the brightness values according to the threshold values of the adjacent masks, and then the brightness value of each pixel is Between the luminance values of the surrounding eight pixels around the pixel, respectively, (1) the luminance values of the surrounding pixels, when equal to the luminance value of the center pixel, and undecided luminance value of the center pixel. (2) When the brightness value of the surrounding pixels is not higher than the brightness value of the central pixel, the brightness value of the central pixel is set to (the intermediate value of the brightness values by the threshold values of the adjacent masks-a) (where a is a positive value). Value). (3) When the brightness value of the surrounding pixels is not lower than the brightness value of the central pixel, the brightness value of the central pixel is set to (the intermediate value of the brightness values by the thresholds of both adjacent masks + a). (4) When the relationship between the brightness values of the surrounding pixels and the brightness value of the central pixel is other than the above relationships (1) to (3), an intermediate value of the brightness values according to the threshold values of both adjacent masks is used. To do. It is determined according to which of the above conditions (1) to (4) is satisfied, and the area center line (skeleton) is extracted for the brightness value undetermined area (brightness value undefined area). ,
After the brightness value of the pixel on the area center line is set to the intermediate value of the brightness values by the threshold values of the adjacent masks, the brightness value of the brightness value undetermined pixel (brightness value undefined pixel) that still remains is the brightness value described above. The brightness value is determined by a linear interpolation method using the brightness value and the distance of the pixels of known brightness at both extension line ends of the undetermined pixel in the fixed direction, or the brightness value of the brightness value undetermined pixel is Determined by the average value of the brightness values obtained by the linear interpolation method using the brightness value and the distance of the pixels of known brightness at both ends of the straight line in each constant direction in each different direction of the pixel whose brightness value is undetermined Or, the brightness value of the remaining brightness value undetermined pixel is determined by the surface interpolation value performed using three pixels whose brightness values in the vicinity of the brightness value undetermined pixel are known, and thus the large image information is obtained. Is being compressed From the image data is than a multi-tone reproduction image is obtained, according to the present invention are conventional problems described above can be satisfactorily solved.

[Brief description of drawings]

FIG. 1 is a block diagram on the compression side in a multidimensional multivalued image compression / decompression system of the present invention.

FIG. 2 is a block diagram showing a configuration example of a predetermined brightness level information extraction unit in the signal processing unit on the compression side.

FIG. 3 is a block diagram showing a configuration example of a contour line tracer in a signal processing unit on the compression side.

FIG. 4 is a block diagram of a polygonal approximate address list in a signal processing unit on the compression side.

FIG. 5 is a block diagram on the decompression side in the multidimensional multi-valued image compression / decompression system of the present invention.

FIG. 6 is a plan view for explaining masks of luminance values having different threshold values.

FIG. 7 is a distribution diagram of luminance values of each pixel of an image.

FIG. 8 is a plan view used for explaining four states defined by a relationship between a luminance value of one pixel in an image and luminance values of eight pixels surrounding the one pixel.

FIG. 9 is a distribution diagram of luminance values of each pixel of an image.

FIG. 10 is a stereoscopic view used for explaining a specific state defined by a relationship between a brightness value of one pixel in an image and brightness values of eight pixels surrounding the one pixel.

FIG. 11 is a diagram used for explaining image expansion.

FIG. 12 is a diagram for explaining a mask of luminance values having different thresholds, and an intermediate level, a high level, and a low level.

FIG. 13 is a diagram showing an example of the distribution of the brightness value of each pixel under a specific condition in the image.

FIG. 14 is a diagram showing an example of distribution of skeletons in an image.

FIG. 15 is a diagram showing an example of the distribution of the brightness value of each pixel under a specific condition in the image.

FIG. 16 is a diagram showing an example of the distribution of the brightness value of each pixel of the reproduced image in the expansion process.

FIG. 17 is a diagram showing an example of the distribution of the brightness value of each pixel of the reproduced image in the expansion process.

FIG. 18 is a diagram showing an example of a distribution of luminance values of pixels of a decompressed reproduced image.

FIG. 19 is a diagram used for explaining an example of determining a brightness value of an unknown pixel.

FIG. 20 is a plan view exemplifying a binary image to be compressed.

FIG. 21 is a plan view showing the contour of a binary image to be compressed.

FIG. 22 is a plan view showing a state in which the contour of the binary image to be compressed is moved so as to pass through the pixel center.

FIG. 23 is a plan view for explaining polygonal approximation of a binary image to be compressed.

FIG. 24 is a plan view illustrating a pixel distribution of a decompressed reproduced binary image.

FIG. 25 is a block diagram showing a configuration example of a contour line tracer.

FIG. 26 is a diagram used for explaining a method of detecting a luminance contour line and a method of determining a feature point.

FIG. 27 is a diagram for explaining luminance function reproduction.

[Fig. 28] Fig. 28 is a diagram for describing luminance function reproduction.

FIG. 29 is a diagram for describing a surface interpolation operation for reproducing a luminance function.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Signal source of the image signal used as the object of multidimensional multi-valued image compression / expansion 2 ... Analog-digital conversion part 3 ... Color memory 4-1-4-n ... Signal processing part 5 ... Predetermined brightness level Information extraction unit, 6 ... Binary memory, 7 ... Contour tracer, 8 ... Contour line address list, 9 ... Polygonal approximate address list, 10 ... Multiplexer, 11 ... Encoding unit and sending unit, 12 ... Transmission line (or recording) Medium), 13 ... reception decoder, 14-1, 14-2 to 14-n ... signal processing circuit, 15, 16, 91 ... end point address register, 17
... local image memory, 18 ... polygon interpolation mask generator, 1
9 ... Multi-value determination operator, 20 ... Skeleton brightness determiner, 21 ... Luminance interpolation plane calculator, 22, 23, 27 ... Image memory, 24 ... Video signal generator, 25 ... Monitor receiver,
28 to 30 ... Address generator, 31 to 33 ... Luminance judging device, 34 to 36 ... Luminance value generating unit, 37 to 39, 93, 9
4 ... Shift register, 40-42 ... Feature point determiner, 43
Alignment circuit 71 Determinator 92 Interpolation address calculator 95 Feature point address register

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Office reference number FI Technical indication location H03M 7/30 Z 8842-5J H04N 1/41 B 7/24 H04N 7/13 Z

Claims (7)

[Claims] 1. A feature point that meets a specific condition for an isoluminance line set for each predetermined specific luminance value in a luminance function of an image is obtained, and the position of the characteristic point of the image and the luminance value are calculated. In a multi-dimensional multi-valued image compression / expansion method used for transmission, recording, and image restoration, at the center position of each pixel forming a specific brightness boundary obtained by tracing the contour of a pixel having a specific brightness value during compression, A multi-dimensional multi-valued image compression / expansion method in which the coordinates of a specific isoluminance line passing point are moved. 2. A characteristic point that meets a specific condition for an equiluminance line set for each predetermined specific luminance value in the luminance function of the image is obtained, and the position and the luminance value of the characteristic point of the image are calculated. In the multidimensional multi-valued image compression / expansion method used for transmission, recording, and image restoration, the above-described isoluminance line is used as a boundary for each threshold value for obtaining the isoluminance line for each specific luminance value during decompression. A multi-dimensional multi-valued image compression / expansion method in which a bright region is filled with a bright symbol, and a dark region bounded by the isoluminance line is filled with a dark symbol to create a mask with a light-dark binary symbol. 3. A characteristic point that meets a specific condition for an equiluminance line set for each predetermined specific luminance value in the luminance function of the image is obtained, and the position and the luminance value of the characteristic point of the image are calculated. In the multi-dimensional multi-valued image compression / expansion method used for transmission, recording, and image restoration, the above-described isoluminance line is used as a boundary for each threshold value for obtaining the isoluminance line for each specific luminance value during decompression. A bright area is filled with a bright symbol, and a dark area bounded by the isoluminance line is filled with a dark symbol to create a mask with a light-dark binary symbol. After arranging and filling the area between the adjacent masks with the intermediate value of the brightness values according to the threshold values of both the adjacent masks, the brightness value of each pixel is set to the periphery 8 with each pixel as the center pixel. Pixel brightness value (1) When the brightness value of the surrounding pixels is equal to the brightness value of the center pixel, the brightness value of the center pixel is undetermined. (2) The brightness value of the surrounding pixels is the brightness value of the center pixel. When it is not higher than the value, the brightness value of the central pixel is set to "the intermediate value-a of the brightness values by the threshold values of the adjacent masks" (where a is a positive value). (3) The brightness values of the surrounding pixels When the brightness value of the center pixel is not lower than the brightness value of the center pixel, the brightness value of the center pixel is set to “the intermediate value + a of the brightness values according to the thresholds of both adjacent masks”. (4) The brightness value of the surrounding pixels and the brightness value of the center pixel When the relationship with is other than the relationships (1) to (3) described above, the intermediate value of the brightness values by the threshold values of the adjacent masks is used, which is shown in the above (1) to (4). It is decided according to which of the conditions is met, and the area center line for the brightness value undetermined area. Extracted and multidimensional multi-valued image compression and decompression method of an intermediate value of the luminance value by the threshold of both the mask adjacent the luminance values of the pixels of the regions centerline. 4. A feature point that meets a specific condition for an isoluminance line set for each predetermined specific luminance value in the luminance function of the image is obtained, and the position and the luminance value of the characteristic point of the image are calculated. In the multi-dimensional multi-valued image compression / expansion method used for transmission, recording, and image restoration, the above-described isoluminance line is used as a boundary for each threshold value for obtaining the isoluminance line for each specific luminance value during decompression. A bright area is filled with a bright symbol, and a dark area bounded by the isoluminance line is filled with a dark symbol to create a mask with a light-dark binary symbol, and the mask is arranged in the order of magnitude of luminance values according to a threshold value. After arranging and filling the area between the adjacent masks with the intermediate value of the brightness values according to the threshold values of both the adjacent masks, the brightness value of each pixel is set to the periphery 8 with each pixel as the center pixel. Pixel brightness value (1) When the brightness value of the surrounding pixels is equal to the brightness value of the center pixel, the brightness value of the center pixel is undetermined. (2) The brightness value of the surrounding pixels is the brightness value of the center pixel. When it is not higher than the value, the brightness value of the central pixel is set to "the intermediate value-a of the brightness values by the thresholds of both adjacent masks" (where a is a positive value). (3) The brightness values of the surrounding pixels When the brightness value of the center pixel is not lower than the brightness value of the center pixel, the brightness value of the center pixel is set to “the intermediate value + a of the brightness values according to the thresholds of both adjacent masks”. (4) The brightness value of the surrounding pixels and the brightness value of the center pixel When the relationship with is other than the above relationships (1) to (3), the intermediate values of the brightness values by the threshold values of both adjacent masks are set, which are shown in the above (1) to (4). It is re-determined according to which of the conditions is met. The core line is extracted, and the brightness value of the pixel on the area center line is set to the intermediate value of the brightness values by the threshold values of the adjacent masks, and the brightness value of the remaining brightness value undetermined pixel is the brightness value undetermined pixel described above. Is a multi-dimensional multi-valued image compression / expansion method in which the brightness value is determined by a linear interpolation method using the brightness value and the distance of pixels of known brightness at both ends of the extension line in the constant direction. 5. The brightness value of the remaining brightness value undetermined pixel is calculated by using the brightness value and the distance of the pixel of known brightness at both ends of the extension line of the straight line in each constant direction in each different direction of the pixel whose brightness value is undetermined. 5. The multi-dimensional multi-valued image compression / expansion method according to claim 4, wherein the multi-dimensional multi-valued image compression / expansion method is determined by an average value of luminance values obtained by the linear interpolation method. 6. The multidimensional multi-valued image according to claim 4, wherein the brightness value of the remaining brightness value undetermined pixel is determined by a surface interpolation value performed using three pixels whose brightness values in the vicinity of the brightness value undetermined pixel are known. Compression / expansion method. 7. The multi-dimensional multi-valued image compression / expansion method according to claim 3, wherein a = d / 3 when the threshold interval between adjacent masks is d.