JPS60150183A - Corrector for digital picture distortion - Google Patents

Abstract

PURPOSE:To correct the density variance of picture data with high accuracy by obtaining a coefficient at each grid point of a split picture for linear approximation and calculating the coefficient at each point from said coefficient at each grid point and the relative coordinates within a block to perform corrections of the digital picture distortion. CONSTITUTION:A picture 21 free from density variance and a picture 23 having density variance are supplied from digital picture input devices 22 and 24 by the control signal given from a processor 25. In this case, a peripheral histogram of a reference point P set on a picture having density variance and a peripheral histogram of a point Q on a picture free from density variance and opposite to the point P are calculated previously by means of the devices 22 and 24. The picture having the density variance is transferred to a picture memory 26 as soon as the histogram is calculated. The processor 25 sends the peripheral histograms of P and Q at grid points that are divided by (mXn) on a picture to a corrector 27 to obtain the coincidence between both histograms. Thus the density variance of pictures can be removed.

Description

[Detailed Description of the Invention] [Field of Application of the Invention] The present invention relates to a digital image distortion correction device. This invention relates to a device that corrects d (light distortion) of an input image by It is necessary to convert the analog signal shown into a digital signal and input it to the d1 calculator. Fig. 1 is a schematic diagram of a conventional image input device. is a sensor, 3 is an analog-to-digital converter, and 4 is a storage device.The radiation intensity of the object L is formed by the sensor 2 as a two-dimensional intensity distribution as shown in the image 8, and the intensity at each point is The analog signal shown in FIG. As shown in FIG. 2, a light ray 11 from an object focuses an image as an electric charge on a photosensitive surface 13 of a vidicon or the like in the focal plane by an optical system 12 such as a lens. 444
B is read out, converted to voltage, and sent out via signal line 1G. By the way, the image captured by the input device shown in FIG. 1 contains uneven shading due to the sensitivity of each point on the photosensitive surface 13 of the sensor 2. In other words, even if a light source with a uniform brightness distribution is used for the subject (1), the shading intensity distribution of the sensor output image 8 or the shading intensity distribution of the image 9 read into the It is not uniform on one surface, but causes unevenness. Therefore, in order to use the image data for accurate analysis and processing, it is necessary to remove this unevenness in shading. In order to do this, as shown in Figure 1, the conversion device 6, storage device 7 and conversion table are
A correction device consisting of an input device 5 is connected downstream of the input device. The conversion device 6 converts each image data obtained in the storage device 4 (l('1), that is, the intensity of the sampled image unit, into an intensity with unevenness removed according to the conversion table.2
The conversion table is used to make the a-dark intensity distribution of the image uniform for the subject 1 of a light source with uniform brightness, and the pixel data converted according to this conversion table is stored in the storage device 7. be damaged. This conversion table is created in the order shown in Fig. 3 (a>(b) (c). For example, the unit is cd), and the input radiation intensity is
Let y be the output cuff 6 pressure appearing on the sensor output signal line 16 that slopes to
The relationship (x, 'y') is obtained at the position on the sensor surface corresponding to b. That is, at each point 17 in FIG. 3('a), the radiation intensity X is varied from 0 to x3. This is S-constant data corresponding to each pixel of one light source when measurement is performed using a light source (<-). The 31st "I (b) is a model of the characteristics of an analog-to-digital converter. The range of sensor output voltage 1/Jl (from 0) is the digital data after conversion when it changes from 0 to If the number of levels is 1-, then the analog-to-digital conversion for the sensor 11 voltage y!I
:+'s output Z is given by the following equation. Z = (1,, , the variable table that can be obtained is as follows: For each point 17 in FIG. -3...(2)
Point +9 indicating the relationship between digital converter output 2 and correction strength U. and a curve 20 connecting points 19. Function 2 obtained by interpolating each point 19 in Figure 3(c)
0 can be calculated using the following equation. u = f(7,) (:s) Also, the conversion table is the level of variable Z, O, I...l, -
1 and is expressed by the linear equation ``C''. 10 minutes
′: Can it be approximated by a linear function with accuracy?1. In this way, for each pixel of the image, the following 1.
By doing °6Ii"r"A+, the desired conversion table is obtained 4
I will. Conversion table? In the conventional method of correcting the 11l pale unevenness of a human image using r, the dull unevenness characteristic of the sensor 2 can be completely determined by U+, and )) This method is based on the premise that the function 1 can be completely modeled. However, in the image data that is actually obtained,
〒The function f that expresses the density cannot be measured or is unknown, or even if the function f is measured once, due to the deterioration of the sensor 2, the characteristics of the uneven shading of the image actually obtained and the uneven shading measured in advance In many cases, the characteristics of the two do not match. For such images, conventional shading unevenness correction methods have the disadvantage that it is difficult to remove shading unevenness. Furthermore, in the conventional method for correcting unevenness in agriculture, it is necessary to prepare a conversion table for each pixel on the screen, and there is also the drawback that the memory capacity becomes large because the conversion table is stored. (Object of the invention) The object of the invention is to solve these drawbacks by
It is possible to correct the filtration distortion of image data where the positive leap number f is not clear (it is possible to correct the filtration distortion of uneven image data, and to reduce the storage space of the conversion table to be memorized, it is possible to correct the filtration distortion of uneven image data at high speed and with high precision. An object of the present invention is to provide a digital image distortion correction device capable of correcting image distortion.
Alternatively, the shading is corrected by using image data that has already been corrected for shading, or by using the point where the shading distortion changes smoothly on a regular videocon camera. It is said that [Embodiments of the Invention] First, a device (first device C'i) that uses image data with little 1J"J light unevenness will be explained, and then next, when such image data is not available, By manually calculating the coefficients of the cotton approximation, 1 agricultural distortion can be effectively reduced by 11
11. The device for correcting (second device) will be explained. First: (At position 11, a reference point P (Q, p) is set on the uneven image to correct uneven shading,
For 1) on an image without uneven shading, p and (a
By matching the histograms of images around
A method is used to remove 'a' and light unevenness in the image. . Now, if the pixel intensity of an image with uneven shading is X, and the pixel intensity of an image without uneven shading is y, then in general, the uneven shading correction function [can be approximated by a linear function with an accuracy of -1 minute, so the following equation holds true. y − a :< + l+ ・ (5) Here, a, 1
] is a picture! The function of horse field (Q, p) = 1 Co,
+ IIL b, (p, , p) can be expressed as −(t
! Then, take the hiss [-gram around 13, set the average as l' At points P and l2, a(1), , p), lJ(+1.p) can be obtained by lj for each of the following people. h (A I 1+) = t, t -t+ (R,
+ p)μ Pixels X and 4 of an image with uneven shading! For pixel y of an image without light unevenness, the average intensity μ7. Figure 4 (
, ) and FIG. 4 0]) 1; Fourth
By subtracting Jξ from the average value ■Σ(y) of the frequency shown in figure (b), the above formula (5) is obtained: y = a x + b...
(5) IE (y) =li (ax+b) IE ((y py )2=E (((ax+b) (
aμx +b)) 2)' -E (F12(X tL
×)2)=a2E (CX p×)2 ) −18) Here, σy 2−(y−pJ)2 ゜, 2 = (, Substituting equation (9) into equation (8), σy 2-n
2σX2"' (10), and the above equation (6) is derived. Also, from q)
+ux has the following relationship according to 1) Expression (5) of II. 71, y: F1μ, + b, −(11) Therefore, the above equation (7) is derived from the equation (11). Next, the process given by the above formula (f;) (7) is performed on the reference point P (Q;, pJ) set in the image with grayscale distortion, and a , (0, □ , PJ) + b
Calculate (Q□, ■・J) and use these values to display the screen,
]− at any point (Q, p)”(QI P)
+b(Q'+p) is calculated by spatial interpolation. Using this a(Q, pL b(Q, p), from the pixel intensity x(A, p) of an image with uneven shading, The uneven pixel intensity "(Q + P) is determined by the following HIE. "(Q, p)=a(D,,p)・x(11,p)+b(
A, p) (12) FIG. 5 is an explanatory diagram of the principle of the present invention, and FIG. 6 is a block diagram of a digital image distortion correction apparatus showing a first embodiment of the present invention. An image 23 with uneven shading and an image 21 without uneven shading in FIG. 6 correspond to (a) and (b) in FIG. 5, respectively. Figure 5 (a) is an image with uneven shading divided into nXm blocks, and the shading distortion is corrected by using the surrounding histodarum for each block and making it correspond to the image in Figure 5 (b). do. aThe image 21 with no unevenness and the image 23 with unevenness are as follows.
A control signal from the processing device 25 is inputted from the digital image human power devices 22 and 24 . At this time, as shown in FIGS. 5(a) and 5(b), j, 4;
The peripheral histogram of point f1 (point 1) (Qi, p, >) and the corresponding peripheral histogram of Q with uneven shading are input into i:lli image IRI using an image input device. Perform one autopsy using 22,2/I. The image with shading (4) is transferred to the rljij image recording device 23 after the Hiss I-gram is calculated by nI (11,1). After inputting the image data, the processing unit 25 extracts the histogram from the image input unit l''t +! (i, j), the variance of the His I-gram σX”NIJ), and the average μ of Q corresponding to 7.1
:V(++JL variance '7:V2N+J) is calculated by 81, and a(i, jL b(i, j) is multiplied by 11t. Next, regarding the histogram around the reference point, FIG.
This will be explained with reference to FIG. As shown in Fig. 7, if we take base iiQ point l] in an image with uneven pixel intensity , in order to take an approximation, when the change is slow, P
Set the region to be wide and narrow when there is a sudden change 1. Set the function y(y+~y,4) at the grid point of the region to a! and other points perform spatial interpolation. ! / l: Il l X+" l + / 2"
, 12 χ→−b2y :l = :r 3:< +)
+:, I, y I= a, 1x + b, 1
(+3) a(i, j), 1) (i, j) is the coefficient % D on the grid point
H. C2+ 'l :J + '] -1+ b 1 r
Using b 2 + ”:4 + bd, stone quality is determined as a hidden line function. Each 8, 1) can be described three-dimensionally at a density level of Q< as shown in Figure 8 (+1) (1). ) has the shape shown in a(1),,p)=ag +al 1-1- C2P+
a3 L・Pl, + (12, P) = βυ + β, L + β2
P+β3L·, P (14) Here, (L, P) are relative positions within the block. In Equation (I4), the coefficient a(A+ r
')+h('l+I)), transfer these to the unevenness correction device Vj27, and transfer the image (et) in the image storage device 2G (11!!) to the unevenness correction device 27. By doing so, the corrected image 28 can be obtained as 1').
+ I'): Niga 1 (
Danmura Fl'l! There are 4 pieces in 1 position on the front side. Processing device Jli (z25 or t) sent I) Incoming message r4II
O is 1.1 (Qr P) l l) C1), , p
The determination circuit 29 determines whether the coefficient of ) is the belief that the opening ri of agricultural 1bi5mu1rauraiL<, 1, and izu';h. . The coefficient of take or a<ay pL b(QI P) is 5
1 (for example, l1lJ′i in the hidden surface line model table 33
Transfer the next data and set the contents of table 33 %, j, ff
1j To be able to stop oil from light unevenness 7) 1-, 1a start light unevenness correction (rJ No. 4(ge, counter: 3)
A signal is sent to 0. When the counter 3 is received, the contents of the counter are cleared to 0 and 1, and the contents of the counter are sequentially increased by 1-. Stop-souga performs the following operations. First, the content K of the counter is Hidden Line Motel Table '3
:3 address 81t is sent to the circuit 32, so the address 81 arithmetic circuit 32 calculates the pixel position (jl, p) on the picture and the corresponding block (i
. j) to stone. ■(=(ρ-)) )
From this, calculate β1 in which block (i, j) that point is included. Then, the address cutting 9 circuit 32 calculates H1 from 71 to address AD of the corresponding table and the relative line 1 in the plotter using the following equation. Δu=(i −1)Xm+j −116) Here, m is the number of blocks in the yellow direction. L = Q, -(i-1) X L B-1...(
17) Here, t and B are the number of lines in the block. As a result of H1 calculation, table address Δ, 1. i
Address register 31 of hidden line model table 33
, it is also sent to the phase + 4 line l, ba; tari calculation) 1 (3・] call and : 35. If you want to make the content of the a1-res register 31, the hidden side model (y) coefficient (t1 + ( '21CL3 + (C4
+ ('L +('2+ β・2.θ, read from the hidden surface line model table 33 and transferred to; Performance 5 in the figure
There are 1ift e configurations of vessels 34 and 35. At 18, I 11, cl+a2L or (1-1-β2L), and C11J0α, 17 or 03+βIL.
, is performed.The value calculated by 31 in the arithmetic circuit 44.45 is α14−+z21.+α3+ regardless of the coefficient +1.
α1■-7 and β1 (-〇, +-+
β3+β, 1■-, and each 4 is 't'r'(W)
) is sent to straddle 36 + 37. Detector/l 3 It, address AD of the hidden surface line model table 33 which is the output of the address word 1 address AD
And the opposite number 53. Detect whether L is the same as the previous one [11. If either one is different from the previous one, operation i! 1; 3 Send the signal -'control' to Fl 1 37, and if it differs, send (No. 0 "o"). The purpose of the detection 8343 is to detect the change of blocks within one line. Performance 21 Book 3 C; increments a(Q+p) by ;:1, and arithmetic unit 371 :):a(Q,p) is multiplied by +tl. Figure 1J is No.! 11! , operation on jl! iB3
37 is an internal configuration diagram. detection! If signal 4G from 43 is 1", select circuit/+91J, operation+iH3'I (or 35
), which is the output of αl−1−ri21, (or β1+
β2[-) is selected, and the selection circuit 50 selects O. At this time, the addition H'rf 52 is (11
1, which outputs the corresponding coefficient when the value of the pixel P is F)=0, and stores (χ3+tr 41- (j5 or β3+β11.) in the register 53 corresponding to the selection circuit 51 (J, gain). 1st phrase, '1 blasphemy (Mate 4: Signal 4 from ball 4 [1 is '' (if 1'', selection V (circuits 49 and 50 are addition)) heel 52 l IiF, I i) The contents of register 5:1, which stores the output contents of the mouth, and the contents of register 5:3, which represents the gain, are selected and added and inputted to 52.The output of adder 52 is This is the claimable coefficient a (or b). Since 111/lN] is an integer, by repeating the addition for that number of times, a
(Q, ,p)=(+z'o 4-α1L)-1-1
)(ζλ2→−αr+L) is 1. The 91st! The first one is so talented? The outputs of the input calculators 3G and 37 are transferred to the input calculator 38 and adder 39, and the image storage μ! 1 place 26
Karaashisu, the image with uneven shading (()
Using the strength
By performing rtij 't3' of x -1-b, the following equation can be subtracted by -1. = a x 1b - (12) 'As mentioned above, is the pixel intensity of i11τ1- and b. The uneven density can be corrected by simply superimposing the intensity of the image on the intensity of the image of the base 7j9, which has no unevenness in l farming method. Next, the second device will be explained. Unlike the first device, the second device can store coefficients based on hidden surface lines in advance without increasing the memory capacity when images without uneven shading cannot be obtained. , with high precision! A: It corrects light unevenness. FIG. 12 is a block diagram of a digital 2r image distortion correction device showing a second embodiment of the present invention. The light from the subject 1 is converted into voltage by the sensor 2 and stored in the storage device 4 via the analog-to-digital converter 63. Correction analog/digital converter 6
3 has a conversion characteristic 57 as shown in FIG.
Performs density unevenness correction at the same time as digital conversion. The conversion characteristics 57 in FIG. 13 are as follows: (1,), (2), (3), (
Using equation 4), it can be calculated as: u=(f(Z)) l111x = (g(y):]...(18) Here, as mentioned above, in a normal vidicon sensor,
[Based on the fact that (Z) can be linearly approximated, rr
(y) can also be linearly approximated. Now, suppose that the linear approximation of g(y) in the above equation (18) is expressed by the following equation. g (y) = a y 1 b ・(19) For each pixel of the human image 55 with uneven shading, the upper 1! g(18)
After converting the shading intensity using the formula, the shading of the image read into the storage device 4 becomes uniform as shown in 5G. Next, a method of sampling the sensor output signal will be explained. The image data that is cursed as an electric shock on the sensor photosensitive surface is the first
As shown in FIG. 4, a total of N lines are read out sequentially from the left side of the screen by l lines by electronic beer l. The read sensor output (i t'359 is a voltage that fluctuates with time as shown in Fig. 15. This is sampled in one cycle of Δt1 to obtain M pixel data per line. .Here, the time during which there is no image data between lines is assumed to be Δt2. FIG. 16 is a block diagram of the correction (Tsanalog-to-digital converter) in FIG. Regarding the above (
The sampler 65 generates the coefficients a and b of formula I9), and the sampler 65 receives the timing signal (
Timing signal every Δt1, but ΔL2 between lines
(there is no signal at ), the output signal of sensor 2 is sampled every 8 t1. 71-Response generation port'J868 is the timing generation circuit 6
7 sends an address (line number Q etc., pixel number l on the line) corresponding to the pixel being sampled to the conversion characteristic generator rti, 60;
The conversion characteristic generator 60 corresponds to the above address (
19) The coefficient a, 1) of equation 1 is calculated and sent to the conversion circuit 6. FIG. 17 is an internal configuration diagram of the conversion circuit 6G that is similar to that shown in FIG.
9) Equation 1] is digital-to-analog conversion 'A'+'
r is converted into an analog signal by 661 and sent to an operational amplifier 663, and d in equation (19) is converted to an analog signal by a digital-to-analog converter 662 and sent to an operational amplifier? ! B 664
``That's it'' and it's sent to you. After that, ll! was sampled with sampler 65. II image data is 8 at the data amplifier 664.
From the multiplied -C, an operational amplifier 663 adds b. After that, Ana 1 with the same characteristics as Figure 3 (I))
i? i
It undergoes a conversion corresponding to equation (18) and is sent to the storage device 4. In this way, the timing signal I'ik
1f (By I+, the gradation distortion h1i positive and the sampling/-5tf- conversion are sequentially performed for each pixel at high speed. Figures 18 and 19 are similar to Figure 16)
I illustrating the principle of creating the conversion characteristics of the i% 45 property generator 60
S〈1, raru. As shown in Figure 133, the screen is divided into r] pieces vertically and horizontally. Divided into 111 parts. It is assumed that the coefficient d, 1] of equation (19) is determined by the method described above at each point of the divided plotter 1. At this time, the pixel 70 (coordinates of (Q
ap)), a and b are determined as follows. . As shown in Figure 15, the size of one block is
3 lines XPT 3 pixels. At this time, the block number (i, j) to which the pixel 70 corresponds is determined by the following equation. Also, the relative coordinates (u, ■) in the blog are expressed by the following formula % Formula % At this time, a and b falling at (+, 1.V) are expressed by the following formula. a (u, v) = tto+tz 1 u+a2 v+
a3 uv (22)1) (IIIV) =βo-1
-βI IJ+β2v-1-β: (uv (23) This parallel line approximation increases the number of divided blocks m, +1 by 1・(
If you set JO number or more), you can use j@kawa function for 16 vidicon cameras. . Here, the coefficients α□, β1 of equations (22) and (23) above are
(1=O, i, '2.3) can be calculated from a, l) measured at the grid points of block division as follows. 1.1', Waino, a□, b4 of each grid point in Figure 19
(i=I), I, two! , 3), it can be obtained by the following equation. +zg Hikitori 0 1 Figure 20 shows the conversion characteristic generator 60 shown in Figure 16.
FIG. Human power; iJ, from device 64, proy'/I3(], +
1. ) l...1'3 (+1. ■), (24) and (25) are the roughly specified coefficients It i . β4 (i = O, 'I, 2.3) is input to the memory 602, and a for the position of the 9th famous painting is
, h are determined as follows: 1 (set). The pixel coordinates (Q
++・Ukara, the address conversion circuit 601 has the above (20
) formula, the 1 cough block measurement number (i, j) is obtained, and the above (2+):iK:
) is a) 5, li V a of the rni notation (:!2) formula corresponding to the block number (i + j');
(i20, ], 2, 3) and the above (2:l
) coefficient β1 (1-0, 1, 2, 3) or memory 602
or 1'', read out, IL, and send to the arithmetic circuits 603 and 60.1, respectively.
The relative coordinate (u, ■) which is the output of 01 is the coefficient Cχ1
．． Using β1, coefficient 8 and coefficient S are calculated according to equations (22) and (23), respectively. This calculated result is sent to the conversion circuit 66. In this way, by storing the predetermined bilinear approximation coefficients α and β1 in the second device, it is possible to record the information for each pixel of an image taken with a vidicon camera, etc. Light distortion compensation 11. and digitization at high speed. [Effects of the Invention] As explained, according to the present invention, IL is
By using an image with less unevenness, or by dividing and storing the coefficient ti for ((j) in advance, !Ij! 1.α is not recorded in the conversion table, etc., so there is no need to increase the memory capacity, and by converting it into a digital signal and inputting it into the digital signal at high speed. , high-speed image f'1M' ``Jj 'J:
; many can be read and processed.

[Brief explanation of the drawing]

Figure 1 is a schematic diagram of a conventional image input device, and Figure 2 is a diagram of a conventional image input device.
Figure 3 is a diagram explaining the creation order of the conversion table in Figure 1, Figure 4 is a diagram showing the principle of the sensor used in the present invention.
A dispersion curve diagram of the inner cable strength of the image, FIG. 5 is a diagram explaining the principle of the present invention, and FIG. 6 is a plotter (ν1, , 1.J
i' (Explanatory diagram of histogram 11 around point Q, Figure 8 (
:] Explanation of the hidden surface line model of the coefficient B+, b (C1, Figure 9 is the shade of Figure +5) Block diagram of the correction device,
101° 4th (Jth) Showa () π (Calculator (34,:
Figure 2 shows the second embodiment of the present invention. Plotter diagram 5 of Shikuru Ryozo Yumi ME device
1; (The figure shows the conversion 1-Ii characteristic in Fig. 12, and Figs. Set 0), il Ming I J,
161”l C 1.2 r31 t:= t+ l
'J Le 111i jl-I: Block diagram of I analog-to-digital converter, No. 17-1 is shown in Fig. 21 is a diagram showing the principle of creating the conversion characteristics of the conversion 1.1 characteristic generator in the 1st I, and FIG. 20 is an internal configuration diagram of the conversion characteristic generator that is added to FIG. 16. Even image, 23: 1 with unevenness
iIiii image, 22.2/I: image fg! Human power equipment, 25:
Processing device, :g to :Image record, α device, 27:Fuhagimura n11 positive 1! 'j, Vfj, 28' tili
iIIE image, 29: Size 5L Fffl m, :(
0: Counter, 3] Near address register, 32 Near address af't"): Circuit, 3: 3 = Paralinear model chifur, to 34 37: Operation H::, 38: Multiplication fli;
, 39: Adder t-1 unit, 44, lI 5: Arithmetic circuit, 'l (], 50.51: Selection circuit, 52: Adder, 53.5/l: Register, 1; : 1: 11
1i positive, I, digital conversion) 1K, 64
: Human power device r'i, 57: Conversion characteristics, 58: Scanning, 59
：Sensor output signal, raO：Conversion characteristic generator, 65：Summerer, 06：Conversion circuit, 67：Timing light regeneration 1(), +; )(Near 1-1 noise generation circuit, 6(3
1, 662: Digital to analog conversion) (: +, 66
3. [36/1: λ amplification) 1:4.665: Analog-to-digital conversion)): (,7 [J: Pixel, 71 to 7
4: Lattice point, 601: AT1F6 conversion circuit, 602: Memory, 603. 6 (l lI nil (t circuit. Fig. 1 100 101 Fig. 2 Fig. 3 (a) (b) (c) Fig. 4 M1xXllyX Fig. 5 m block Fig. 6) 7 diagram Fig. 8 (a) (L, P, ) (L2P,) (b) Figure 9aa:<+b 1st (]χ1 α1+α2L αke αlI. ir 1 1 ::!1 1214th 13th:χ; Se/ Output City IE (yf No. 14 '>j to'!■5;4 85Z1t No. 161:4 Ushi No. 171' (1 az Figure 19 No. 201χ1 Continuation of page 1 0 Inventor Akira Tsuboi @ Inventor Hiroshi Ihara - [Phase] Inventor Yutaka Kubo 109 Hata, Ozenji, Asao-ku, Kawasaki-shi Hitachi, Ltd. System Hitachi University, Mika-cho 5-2-1 Hitachi, Ltd. Omika Factory

Claims (3)

[Claims] (1) A means for inputting an image containing light unevenness, and after or at the same time converting the image signal of the input image from analog to digital, dividing the input image into a plurality of blocks, and dividing the input image into a plurality of blocks, and each grid point of the block. 1. A digital image distortion correction device, comprising means for determining a coefficient for approximating a hidden surface line, calculating a coefficient for each point based on the coefficient and relative coordinates within the block, and correcting light unevenness. (2) Feature a' (Claim No. 11 rrf
A digital image distortion correction apparatus as described. (3) When calculating coefficients for hidden surface line approximation at each grid point of the block, calculate the coefficients in advance and use analog
2. The digital image distortion correction device according to claim 1, wherein the digital image distortion correction device is stored in a memory of the digital conversion device Takeuchi.