Method for compensating pixel interference of image

A method for compensating a pixel of an image is provided The method includes using four median value extraction matrices to obtain the edge information of the image, where the edge information obtained by two of the matrices is Gb value, and the edge information obtained by the other two matrices is Gr value, calculating the corresponding average values of the Gb and Gr values, multiplying a differential value between the average value of the Gb value and the average value of the Gr value with a proportion value to obtain a compensation value, and adding the compensation value to or subtracting the compensation value from the original Gb and Gr values to obtain compensated Gb and Gr values.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan application serial no. 95133604, filed on Sep. 12, 2006. All disclosure of the Taiwan application is incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image processing method. More particularly, the present invention relates to an image processing method for solving pixel interference of an image.

2. Description of Related Art

FIG. 1is a block diagram of the circuit of a conventional image capturing device. Referring toFIG. 1, an image sensing module includes an image sensing device10, an analog control circuit11, and an analog-to-digital signal converter12. An image signal processor includes an image sensing device compensator13, a color interpolation device14, and an image quality enhancing device15. The image sensing device10includes a condensing lens16, a color filter array17, and a photo-diode18. As each pixel corresponds to a color in the color filter array17, the image sensing module will output Bayer array data19.

In the conventional art, such as the interpolation method disclosed by W. Li et al. (W. Li, P. Ogunbona, Y. Shi, and I. Kharitonenko, “CMOS Sensor Cross-Talk Compensation for Digital Cameras”, IEEE Trans. on Consumer Electronics, Vol. 48, No. 2, pp. 292-297, May 2002), G7pixel in the Bayer array data shown inFIG. 3is regarded as a Gr pixel to be compensated, and the compensated G7newis calculated according to the formulae below.
Gnew7=G7+ΔG
where
ΔG7=(ΔG4+ΔG5+ΔG9+ΔGa)/4
ΔG4=G4−(G1+G2+G6+G7)/4
ΔG5=G5−(G2+G3+G7+G8)/4
ΔG9=G9−(G6+G7+Gb+Gc)/4
ΔGa=Ga−(G7+G8+Gc+Gd)/4

According to the above formulae, it is known that the compensation value is an average value of four surrounding Gb differential values, where each Gb differential value is obtained by subtracting the average value of four surrounding Gr values. As this method captures a great quantity of surrounding pixels to calculate the average values, when tiny line structures fall in the region, false color occurs around the lines and on the lines. Meanwhile, this method compensates one of the Gr or Gb pixels only, which makes the entire compensated image tend to be bluish or reddish. Moreover, W. Li et al. disclosed a second average value method in the same paper. Though the Gb and Gr pixels are compensated at the same time, this average value method still captures a great quantity of surrounding pixels to calculate the average values, and causes false color in tiny structures as well.

In addition, the interpolation method disclosed by C. Weerasinghe et al. (C. Weerasinghe, I. Kharitonenko, and P. Ogunbona, “Method of Color Interpolation in a Single Sensor Color Camera Using Green Channel Separation”, IEEE Proceeding 2002, pp. 3233-3236, 2002) regards a G7pixel30in Bayer array data shown inFIG. 3as a Gr pixel to be compensated, and the compensated G7newis calculated according to the formula below.

G7new=G7+SMF⁡(G4,G5,G9,Ga,G7)2
where, SMF (standard median filter) stands for a median value extraction filter. Therefore, a compensation value is obtained by extracting the median value of the G7and the four surrounding Gb, and then the G7newis an average value of the median value and the G7. This method often extracts wrong median for tiny line structures, thus causing false color in the tiny line structures as well.

SUMMARY OF THE INVENTION

The present invention is directed to a method for compensating image array data, which effectively solves the problems concerning color deviation of images and false colors on tiny line structures or edges thereof. The image array data comprises a plurality of color pixels, and the color pixels at least comprise a plurality of first color pixels.

The method for compensating image array signals provided by the present invention comprises the following steps. One of the first color pixels is selected for further compensation. The color pixels horizontally adjacent to the selected first color pixel are second color pixels, and the color pixels vertically adjacent to the selected first color pixel are third color pixels. In addition, the first color pixels horizontally adjacent to the second color pixels in a predetermined region around the selected first color pixel are operated to obtain a first average value. Similarly, the first color pixels horizontally adjacent to the third color pixels in the predetermined region are operated to obtain a second average value. Thus, the present invention obtains a compensation value according to the first average value and the second average value, so as to compensate the selected first color pixel.

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

DESCRIPTION OF EMBODIMENTS

FIG. 4is a 5×5 Bayer array data40. Referring toFIG. 4, the present invention uses four standard median filters to obtain tiny components β1, β2, β3, and β4, which are obtained by the following formulas.
β1=SMF(Gb02,Gb20,Gb22,Gb24,Gb42)
β2=SMF(Gb00,Gb04,Gb22,Gb40,Gb44)
β3=SMF(Gr11,Gr13,Gr33)
β4=SMF(Gr11,Gr31,Gr33)

Here, SMF refers to the operation of extracting the median value. Assuming Gb02>Gb20>Gb22>Gb24>Gb42, the output of the standard median filter is Gb22. Similarly, persons of ordinary skill in the art can sequentially determine the values of β2, β3, and β4. β1and β2reveal the edge information of the Gb pixels in this embodiment. On the other hand β3and β4reveal the edge information of the Gr pixels in this embodiment. Through the filter element distribution of the four standard median filters, the components of the tiny line structures falling in the Gb and Gr pixels are obtained respectively. Regardless whether the line structures in this embodiment are straight lines, oblique lines, right angles, V-shaped lines, or any other polygons, the tiny components of the Gb and Gr pixels can be obtained using the four standard median filters.

Then, the average value of β1and β2of the Gb pixels is obtained, i.e., the average value of the tiny structures in the Gb pixels is obtained, which is represented by d1as follows.

d1=(β1+β2)2
similarly, the average value of β3 and β4 of the Gr pixels is obtained, i.e., the average value of the tiny structures in the Gr pixels is obtained, which is represented by d2as follows.

d2=(β3+β4)2
Then the compensated Gb22is calculated according to the formula below.
Gb22new=Gb22+(d2−d1)/2
The components of each of the compensated Gb and Gr pixels can be obtained by repeating the above steps.

To sum up, the method of the present invention compensates the interference of the pixels of the image sensor in the regions with uniform and smooth colors, on the tiny line structures and on the edges thereof, so as to suppress the occurrence of the false colors.