Black and white stretching system and method for improving contrast of a picture

• US 20050031200A1
• Filed: 04/23/2004
• Published: 02/10/2005
• Est. Priority Date: 08/09/2003
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Lee, Sang-soo, Lee, Ho-nam
• Granted Patent: US 7,292,734 B2
• Time in Patent Office: Days
• US Class Current: 382/169
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/92 based on global image properties

Abstract

A black and white stretching system and method for improving contrast of a picture is disclosed. The system includes a histogram distribution calculation unit for calculating a histogram distribution of an input signal of a specified unit, a mean calculation unit for calculating a mean level of the input image signal, a slope calculation unit for calculating black and white stretching slopes in association with the mean level, a ratio calculation unit for calculating a ratio of a picture change based on the histogram distribution of the present input image signal and the previous input image signal, a filtering unit for adjusting the black and white stretching slopes corresponding to the ratio of the picture change, and a stretching unit for stretching the input image signal by mapping the adjusted black and white stretching slopes and the input image signal.

Claims

1. A black and white stretching system comprising:

a histogram distribution calculation unit for calculating a histogram distribution of an input signal of a specified unit;

a mean calculation unit for calculating a mean level of the input image signal;

a slope calculation unit for calculating black and white stretching slopes in association with the mean level;

a ratio calculation unit for calculating a ratio of a picture change on the basis of the histogram distribution of the present input image signal and a previous input image signal;

a filtering unit for adjusting the black and white stretching slopes corresponding to the ratio of the picture change; and

a stretching unit for stretching the input image signal by mapping the adjusted black and white stretching slopes and the input image signal.

2. The system as claimed in claim 1, wherein

the histogram distribution calculation unit detects a sum of whole levels of the input image signal and the total number of pixels, and

the mean calculation unit calculates the mean level of the input image signal using the sum of whole levels and the total number of pixels.

3. The system as claimed in claim 1, wherein

the histogram distribution calculation unit detects a maximum level and a minimum level of the input image signal, and

the slope calculation unit calculates black and white stretching points, L_B and L_W, using the maximum level, the minimum level, the mean level, and preset stretching points.

4. The system as claimed in claim 3, wherein the black and white stretching points L_B and U_W calculated by the slope calculation unit are expressed by the following equations

$L_B=L+\frac{M-L}{T}$ $U_W=U+\frac{M-U}{T}$

where, L and U are the preset black and white stretching points, M is the mean level, and T is an association parameter.

5. The system as claimed in claim 3, wherein the slope calculation unit calculates the black and white stretching slopes in association with the mean level using the calculated black and white stretching points, the minimum level, and the maximum level.

6. The system as claimed in claim 1, further comprising

a histogram information calculation unit for calculating histogram information data, Diff_histo, using the histogram distribution of the present input image signal and the previous input image signal calculated by the histogram distribution calculation unit;

wherein the ratio calculation unit calculates the ratio of the picture change using the histogram information data, and provides the ratio of the picture change to the filtering unit.

7. The system as claimed in claim 6, wherein the histogram information data, Diff_histo, calculated by the histogram information calculation unit is given by the following equation

$\mathrm{Diff}$

- ⁢

histo = ∑

i = m n ⁢

( H ⁡

( i ) C - H ⁡

( i ) P )

where, H(i)_P is the histogram distribution of the previous image signal, H(i)_C is the histogram distribution of the present image signal, i is a gray level, and n and m are natural numbers.

8. The system as claimed in claim 6, wherein the ratio of the picture change (Coeff) calculated by the ratio calculation unit is given by the following equation

$\mathrm{Coeff}=\frac{\mathrm{Diff}}{}$

- ⁢

histo Total

where, Total is the total number of pixels of the input image signal.

9. The system as claimed in claim 6, wherein the filtering unit adjusts the present black and white stretching slopes such that if the ratio of the picture change is small, the filtering unit reflects the previous black and white stretching slopes corresponding to the previous input image signal relatively large in comparison to the present black and white stretching slopes corresponding to the present input image signal, and such that if the ratio of the picture change is large, the filtering unit reflects the present black and white stretching slopes corresponding to the present input image signal relatively large in comparison to the previous black and white stretching slopes corresponding to the previous input image signal.

10. A black and white stretching method comprising:

a histogram distribution calculation step of calculating a histogram distribution of an input signal of a specified unit;

a mean calculation step of calculating a mean level of the input image signal;

a slope calculation step of calculating black and white stretching slopes in association with the mean level;

a ratio calculation step of calculating a ratio of a picture change on the basis of the histogram distribution of the present input image signal and a previous input image signal;

a filtering step of adjusting the black and white stretching slopes corresponding to the ratio of the picture change; and

a stretching step of stretching the input image signal by mapping the adjusted black and white stretching slopes and the input image signal.

11. The method as claimed in claim 10, wherein

the histogram distribution calculation step detects a sum of whole levels of the input image signal and the total number of pixels, and

the mean calculation step calculates the mean level of the input image signal using the sum of whole levels and the total number of pixels.

12. The method as claimed in claim 10, wherein

the histogram distribution calculation step detects a maximum level and a minimum level of the input image signal, and

the slope calculation step calculates black and white stretching points using the maximum level, the minimum level, the mean level, and preset stretching points.

13. The method as claimed in claim 12, wherein the black and white stretching points, L_B and U_W, calculated at the slope calculation step are expressed by the following equations

$\begin{array}{c}{L}_B=L+\frac{M-L}{T}\\ U_W=U+\frac{M-U}{T}\end{array}$

where, L and U are the preset black and white stretching points, M is the mean level, and T is an association parameter.

14. The method as claimed in claim 12, wherein the slope calculation step calculates the black and white stretching slopes in association with the mean level using the calculated black and white stretching points, the minimum level, and the maximum level.

15. The method as claimed in claim 10, further comprising:

a histogram information calculation step of calculating histogram information data using the histogram distribution of the present input image signal and the previous input image signal calculated at the histogram distribution calculation step;

wherein the ratio calculation step calculates the ratio of the picture change using the histogram information data, and the filtering step adjusts the black and white stretching slopes on the basis of the ratio of the picture change.

16. The method as claimed in claim 15, wherein the histogram information data, Diff_histo, calculated at the histogram information calculation step is given by the following equation

$\mathrm{Diff}$

- ⁢

histo = ∑

i = m n ⁢

( H ⁡

( i ) C - H ⁡

( i ) P )

where, H(i)_P is the histogram distribution of the previous image signal, H(i)_C is the histogram distribution of the present image signal, i is a gray level, and n and m are natural numbers.

17. The method as claimed in claim 15, wherein the ratio of the picture change (Coeff) calculated at the ratio calculation step is given by the following equation

$\mathrm{Coeff}=\frac{\mathrm{Diff}}{}$

- ⁢

histo Total

where, Total is the total number of pixels of the input image signal.

18. The method as claimed in claim 15, wherein the filtering step adjusts the present black and white stretching slopes such that if the ratio of the picture change is small, the filtering step reflects the previous black and white stretching slopes corresponding to the previous input image signal relatively large in comparison to the present black and white stretching slopes corresponding to the present input image signal, and such that if the ratio of the picture change is large, the filtering step reflects the present black and white stretching slopes corresponding to the present input image signal relatively large in comparison to the previous black and white stretching slopes corresponding to the previous input image signal.