Method of and apparatus for processing image data

• US 6,424,747 B1
• Filed: 11/17/1998
• Issued: 07/23/2002
• Est. Priority Date: 11/20/1997
• Status: Expired due to Term

• Current Assignee: Fujifilm Corporation (Fujifilm Holdings Corporation)
• Original Assignee: Fuji Photo Film Co Limited (Fujifilm Holdings Corporation)
• Inventors: Morikawa, Seiichiro
• Primary Examiner(s): GRANT II, JEROME
• Application Number:
  US09/193,716
• Time in Patent Office: 1,344 Days
• Field of Search: 382/210, 382/260, 382/261, 382/262, 382/263, 382/264, 358/518, 358/521, 358/522, 358/523, 358/524, 358/530, 358/532
• US Class Current: 382/210
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: H04N 1/58 Edge or detail enhancement; Noise or error suppression, e.g. colour misregistration correction H04N1/62 takes precedence
• CPC Class Codes: H04N 1/6019 using look-up tables H04N1/6025 takes precedence

Abstract

A smoothing circuit smoothes lookup tables generated by a color conversion table generator, using a filter function selected from a filter function storage circuit, and supplies smoothed lookup tables to a color processing circuit. Density data supplied from a calibration circuit are converted into halftone dot % data according to the smoothed lookup tables. The halftone dot % data are interpolated and then converted into LD control data, which are supplied to laser diodes.

Claims

1. A method of processing image data, comprising the steps of:

smoothing conversion data established according to predetermined image processing conditions, using a predetermined filter function selected by user there by producing new conversion data; and

converting input image data into output image data using said new conversion data;

wherein said step of smoothing conversion data comprises the steps of;

determining a histogram in an input signal space from said input image data;

weighting said filter function based on said histogram;

smoothing more frequent data of said input image data more intensively; and

smoothing less frequent data of said input image data less intensively.

2. A method according to claim 1, wherein said histogram is generated by dividing said input signal space into a plurality of regions and determining a count of input image data in each of said regions with respect to an average count of the input image data with respect to said regions.

3. A method according to claim 2, wherein said regions include smaller regions with respect to a highlight zone of the input image data and larger regions with respect to a shadow zone of the input image data.

4. A method according to claim 1, wherein said new conversion data T′

j (C, M, Y) are determined from the conversion data Tj (C+dC, M+dM, Y+dY) to be smoothed, using said filter function Ap (dC, dM, dY) and a weighing function W (C, M, Y) for weighting the filter function Ap (dC, dM, dY) based on said histogram, as follows;

$<br><br>\begin{array}{c}{T}^{\mathrm{\prime <br><br>}}<br><br>j<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)=\frac{\begin{array}{c}\sum <br><br>\underset{\mathrm{dC},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dM},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dY}=-1}{\overset{1}{\sum <br><br>}}<br><br>\sum <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{Tj}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C+\mathrm{dC},M+\mathrm{dM},Y+\mathrm{dY}\right)·<br><br>\\ \mathrm{Ap}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{dC},\mathrm{dM},\mathrm{dY}\right)·<br><br>W<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)\end{array}}{b<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)}\\ b<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)=\sum <br><br>\underset{\mathrm{dC},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dM},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dY}=-1}{\overset{1}{\sum <br><br>}}<br><br>\sum <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{Ap}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{dC},\mathrm{dM},\mathrm{dY}\right)·<br><br>W<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)\end{array}$

5. A method of processing image data, comprising the steps of:

establishing predetermined color conversion functions using designated data and test density data selected by a user;

generating color conversation data with a color conversion table generator using said color conversion functions;

smoothing said conversion data using a predetermined filter function selected by the user, thereby producing new conversion data; and

converting input image data into output image data using said new conversion data,

wherein said filter function comprises a function having filter coefficients for smoothing attentional input image data with input image data around the attentional input image data.

6. A method according to claim 5, wherein said filter coefficients comprise coefficients for averaging the attentional input image data with the input image data around the attentional input image data.

7. A method according to claim 5, wherein said filter coefficients comprise coefficients for weighting said filter function around the attentional input image data.

8. A method of processing image data, comprising the steps of:

smoothing conversion data established according to predetermined image processing conditions, using a predetermined filter function thereby producing new conversion data; and

converting input image data into output image data using said new conversion data;

wherein said new conversion data T′

j (C, M, Y) are determined from the conversion data Tj (C+dC, M+dM, Y+dY) to be smoothed, using said filter function Ap (dC, dM, dY), as follows;

$T^{\mathrm{\prime <br><br>}}<br><br>j<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C,M,Y\right)=\frac{\begin{array}{c}\sum <br><br>\underset{\mathrm{dC},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dM},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dY}=-1}{\overset{1}{\sum <br><br>}}<br><br>\sum <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{Tj}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(C+\mathrm{dC},M+\mathrm{dM},Y+\mathrm{dY}\right)·<br><br>\\ \mathrm{Ap}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{dC},\mathrm{dM},\mathrm{dY}\right)\end{array}}{a},$

where $a=\sum <br><br>\underset{\mathrm{dC},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dM},\text{\hspace{1em}<br><br>}<br><br>\mathrm{dY}=-1}{\overset{1}{\sum <br><br>}}<br><br>\sum <br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{Ap}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{dC},\mathrm{dM},\mathrm{dY}\right).$

9. A method of processing image data, comprising the steps of:

smoothing conversion data established according to predetermined image processing conditions, using a predetermined filter function, thereby producing new conversion data;

converting input image data into output image data using said new conversion data;

displaying an image based on said input image data;

designating a point on the displayed image; and

weighting said filter function around a portion of said input image data which corresponds to the designated point (x, y);

wherein said weighting function W (C, M, Y) for weighting the filter function is defined as follows;

10. A method of processing image data, comprising the steps of:

smoothing conversion data established according to predetermined image processing conditions, using a predetermined filter function, thereby producing new conversion data;

converting input image data into output image data using said new conversion data;

displaying an image based on said input image data;

designating a point on the displayed image; and

weighting said filter function around a portion of said input image data which corresponds to the designated point (x, y);

wherein said weighting function W (C, M, Y) for weighting the filter function is defined as follows;

11. An apparatus for processing image data, comprising:

a conversion data generator for generating color conversion data, said color conversion data being established using predetermined color conversion functions determined from designated data and test density data selected by a user;

a filter function storage circuit for storing a filter function selected by the user;

a smoothing circuit for smoothing said conversion data using said filter function, thereby producing new conversion data; and

a processing circuit for converting input data into output image data using said new conversion data;

wherein said conversion data generator comprises a shadow and highlight density setting unit receiving a density setting value supplied by a user to normalize densities in the input image.

12. The apparatus of claim 11, wherein said conversion data generator further comprises a signal arranging calculator receiving an output of the shadow and highlight density setting unit to determine a minimum and maximum value of density.

13. The apparatus of claim 12, wherein said conversion data generator further comprises a halftone gray balance circuit using a result of the signal arranging calculator and further receiving a user input to provide gray balance data used in generating said color conversion data.

14. The apparatus of claim 13, wherein said test density data comprises the input image data with changes in selected levels of the input image.

15. A method of processing image data, comprising the steps of:

establishing predetermined color conversion functions using designated data and test density data selected by a user;

generating color conversation data with a color conversion table generator using said color conversion functions;

smoothing said conversion data using a predetermined filter function selected by the user, thereby producing new conversion data; and

converting input image data into output image data using said new conversion data,

further comprising;

receiving a user input to provide gray balance data used in generating said color conversion data.

16. The method according to claim 15, wherein said test density data comprises the input image data with changes in selected levels of the input image.

17. The method according to claim 16, wherein said smoothing comprises:

determining a histogram in an input signal space from said input image data;

smoothing more frequent data of said input image data more intensively and smoothing less frequent data of said input image data less intensively.