Digital focusing method and apparatus in image processing system

Claim 2

A digital focusing method in an image processing system, comprising the steps of: dividing a defocused image into sub-images of a predetermined size; estimating an edge direction of each of the divided sub-images; calculating step responses for respective edge directions; obtaining a mean step response by averaging a predetermined number of the step responses; obtaining Point Spread Function (PSF) coefficients using the mean step response; obtaining an image blur transfer function using the PSF coefficients; obtaining an image restoration transfer function using the image blur transfer function; and obtaining an in-focused image by multiplying the image restoration transfer function by the defocused image in a frequency domain.

Claim 3

The method according to claim 1, wherein said PSF coefficients are: ##EQU9## wherein R is a radius of the PSF, Z is a value obtained by subtracting a minimum value of the mean step response from a maximum value thereof.

Claim 4

The method according to claim 2, wherein said step of obtaining an image blur transfer function includes arranging the coefficients of the PSF in a spatial domain: ##EQU10## and; performing DFT on h.

Claim 5

The method according to claim 3 wherein said step of obtaining image restoration transfer function G is by: ##EQU11## wherein H is said image blur transfer function, H* is a complex conjugate of H and C' is a function of a linear high pass filter.

Claim 6

The method according to claim 4, wherein said image is focused by inversely discrete-Fourier-transforming G, with an out-of-focus image signal.

Claim 7

The method according to claim 1, wherein said defocused image is focused in real time.

Claim 8

The method according to claim 1, wherein said step of estimating edge direction comprises the substeps of: (a1) obtaining two discrete cosine transform coefficients Cv and Ch respectively representing vertical and horizontal edges; (a2) determining whether the absolute values of Cv and Ch are both smaller than a predetermined critical value Th; (a3) estimating the edge direction to be monotonous if the absolute values of Cv and Ch are both smaller than the predetermined critical value Th; (a4) determining whether a value obtained by subtracting the absolute value of Cv from the absolute value of Ch is larger than Th, if the absolute values of Cv and Ch are not both smaller than the predetermined critical value Th; (a5) estimating the edge direction to be horizontal if the result of the subtraction of step (a4) is lager than Th; (a6) determining whether a value obtained by subtracting the absolute value of Ch from the absolute value of Cv is larger than Th, if the value of the subtraction of step (a4) is no larger than Th; (a7) estimating the edge direction to be vertical if the result of the subtraction in step (a6) is larger than Th; (a8) determining whether the product of Ch and Cv is positive, if the result of the subtraction in step (a6) is not larger than Th; (a9) estimating the edge direction to be 45°, if the product in step (a8) is positive; and (a10) estimating the edge direction to be 135°, if the product in step (a8) is not positive, wherein the steps (a1) through (a10) are performed on each of the sub-images.

Claim 9

The method according to claim 1, wherein said step of estimating edge direction includes calculating DCT coefficients Cv and Cn for vertical and horizontal edges, respectively.

Claim 10

The method according to claim 8, further including the step of classifying edge directions into one of monotone, horizontal, vertical and angular directions by comparing mathematical functions of Cv and Cn to predetermined thresholds.

Claim 11

An image processing device having a processor and associated memory, comprising: means for dividing a defocused image into sub-images of a predetermined size; means for estimating an edge direction of each of the divided sub-images; means for calculating step responses for respective edge directions; and means for obtaining a mean step response by averaging a predetermined number of the step responses, obtaining Point Spread Function (PSF) coefficients using the mean step response, obtaining an image blur transfer function using the PSF coefficients, obtaining an image restoration transfer function using the image blur transfer function, and obtaining an in-focused image by multiplying the image restoration transfer function by the defocused image in a frequency domain.

Claim 12

An image processing device having a processor and associated memory, comprising: means for dividing a defocused image into sub-images of a predetermined size; means for estimating an edge direction of each of the divided sub-images; means for calculating step responses for respective edge directions; and means for obtaining a mean step response by averaging a predetermined number of the step responses, obtaining Point Spread Function (PSF) coefficients using the mean step response, obtaining an image blur transfer function using the PSF coefficients, obtaining an image restoration transfer function using the image blur transfer function, and obtaining an in-focused image by multiplying the image restoration transfer function by the defocused image in a frequency domain.

Claim 13

The device according to claim 10, wherein said PSF coefficients are: ##EQU12## wherein R is a radius of the PSF, Z is a value obtained by subtracting a minimum value of the mean step response from a maximum value thereof.

Claim 14

The device according to claim 11, wherein said means for obtaining an image blur transfer function includes means for arranging the coefficients of the PSF in a spatial domain: ##EQU13## and; performing DFT on h.

Claim 15

The device according to claim 12 wherein said means for obtaining image restoration transfer function G is by: ##EQU14## wherein H is said image blur transfer function, H* is a complex conjugate of H and C' is a function of a linear high pass filter.

Claim 16

The device according to claim 13, further including means for inversely discrete-Fourier-transforming G with an out-of-focus image signal for outputting a focused image.

Claim 17

The device according to claim 10, wherein said defocused image is focused in real time.

Claim 18

The device according to claim 10, wherein said defocused image is focused in less than 100 milliseconds.

Claim 19

The device according to claim 10, wherein said means for estimating edge direction includes means for calculating DCT coefficients Cv and Cn for vertical and horizontal edges, respectively.

Claim 20

The device according to claim 17, wherein said means for estimating edge direction further includes means for classifying edge directions into one of monotone, horizontal, vertical and angular directions by comparing mathematical functions of Cv and Cn to predetermined thresholds.

Claim 21

An image focusing device comprising: a transfer function calculator for calculating PSF coefficients and calculating an image blur transfer function represented in a frequency domain; a first absolute value calculator for calculating the absolute value of the input image blur transfer function; a first squarer for squaring the absolute value of the blur transfer function; a complex conjugate calculator for calculating a complex conjugate of the image blur transfer function; a second absolute value calculator for calculating the absolute value of a predetermined input operator; a second squarer for squaring the absolute value of the predetermined operator; a first multiplier for multiplying the output of the second squarer by a Lagrange multiplier; an adder for adding the output of the first multiplier to the output of the first squarer; a divider for dividing the output of the adder by the complex conjugate and outputting an image restoration transfer function; and a second multiplier for multiplying the image restoration transfer function by an out-of-focus image represented in the frequency domain, and outputting the product as an in-focused image.

Claim 22

An image focusing device comprising: a transfer function calculator for calculating PSF coefficients and calculating an image blur transfer function represented in a frequency domain; a first absolute value calculator for calculating the absolute value of the input image blur transfer function; a first squarer for squaring the absolute value of the blur transfer function; a complex conjugate calculator for calculating a complex conjugate of the image blur transfer function; a second absolute value calculator for calculating the absolute value of a predetermined input operator; a second squarer for squaring the absolute value of the predetermined operator; a first multiplier for multiplying the output of the second squarer by a Lagrange multiplier; an adder for adding the output of the first multiplier to the output of the first squarer; a divider for dividing the output of the adder by the complex conjugate and outputting an image restoration transfer function; and a second multiplier for multiplying the image restoration transfer function by an out-of-focus image represented in the frequency domain, and outputting the product as an in-focused image.

Claim 23

The device according to claim 19, wherein said PSF coefficients are: ##EQU15## wherein R is a radius of the PSF and S(X) [1≦X≦R] denotes a mean step response, and Z is a value obtained by subtracting a minimum value of the mean step response from a maximum value thereof.

Claim 24

The device according to claim 20, wherein said out-of-focus image is outputted as in-focused image in real time.