KR20060069190A - Method and device for processing image of plasma display panel - Google Patents

Abstract

The present invention relates to an image processing method and an image processing apparatus of a plasma display panel. The image processing apparatus and the image processing method of the present invention are characterized by analyzing the input gray level signal to classify objects and filtering by varying the size of the filter according to the size of the object. As described above, the present invention can prevent deterioration of resolution by dividing an object from an object and filtering a region of each object by varying the size of a filter.

Description

Image processing method and image processing apparatus of a plasma display panel {Method and Device for Processing Image of Plasma Display Panel}

1 (a) and 1 (b) are for explaining the difference in the amount of light of each grayscale according to the change in peak luminance of the plasma display panel.

2 is for explaining the basic concept of the image processing method for improving the gradation linearity.

3 illustrates an embodiment of an image processing method using high boost filtering.

4 is an example of a two-dimensional mask for high boost filtering.

5 shows filtering used for peaking filtering.

6 is for explaining a problem that occurs when filtering is performed using a mask having the same size.

7 is a block diagram of an image processing apparatus according to the present invention.

8 to 10 are for explaining the operation of the image processing apparatus according to the present invention.

The present invention relates to a plasma display panel, and more particularly, to an image processing method and an image processing apparatus of a plasma display panel.

1 (a) and 1 (b) are for explaining the difference in the amount of light of each grayscale according to the change in peak luminance of the plasma display panel. 1 (a) shows the amount of light for each of 256 gray levels when the peak luminance is 500 cd / m 2. FIG. 1B shows the amount of light for each of 256 gray levels when the peak luminance is 1000 cd / m 2.

When the peak luminance is 500 cd / m 2 and the gray level is 256, the light quantity difference between each gray level is 1 to 2 cd. However, when the peak luminance is 1000 cd / m 2 and the gradation is 256, the light quantity difference between each gradation is 3 to 4 cd.

If the light quantity difference between each gray scale is small, as shown in FIG. 2A, the light quantity change in each gray scale is natural to the human eye. However, when the light quantity difference between the gray scales is large, the light quantity change in each gray scale is large, and therefore, a step may appear to the human eye as shown in FIG.

As the luminance of the plasma display panel increases, a problem in that gray linearity and gray expression power become worse when the light quantity difference between the gray scales increases.

In addition, conventionally, in order to convert an 8-bit gradation signal to 8 bits or more, there has been a method of simply mapping scaling or gamma to 8 bits or more and a method using a decimal point. However, the above methods have a problem in that the number of bits to be expressed increases but the number of gray levels that can be actually expressed does not increase.

2 is for explaining the basic concept of the image processing method for improving the gradation linearity. As shown in FIG. 2, since the light quantity difference between each gray scale is large, gray scale expression is divided again between gray scales and gray scales.

For example, since the difference between the amounts of light of each of the 127 and 128 gradations is large, 127.25, 127.50, and 127.75 gradations are generated by dividing the 127 and 128 gradations, which are 8-bit image signals, into four equal parts.

In this case, a filtering mask is used to divide the gray level from the gray level. For example, Gaussian filtering, high boost filtering, peaking filter, and the like may be used. That is, the gray scale expression power and the gray linearity may be improved by having 256 or more gray scales that are actually expressed using the image information. The method of improving gray scale expression power is defined as GUC (Gradation Up Conversion).

3 illustrates an embodiment of an image processing method using high boost filtering. As shown in FIG. 3, high boost filtering is used to divide between gray scales. The high boost filtering will be described in detail with reference to FIG. 3 and Equation 1 below.

  High boost = (A) (Original)-Lowpass

            = (A-1) (Original) + Original-Lowpass

            = (A-1) (Original) + Highpass

Here, A is a gain, and Original means an original signal of 8 bits or 10 bits. 10 bits is a signal scaled by a linear scaler. Lowpass means low frequency component. Highpass means high frequency components. That is, the high boost filtering increases the sharpness by obtaining a signal as shown in FIG. 3C by adding a high frequency component as shown in FIG. 3B to an original signal as shown in FIG. 4 is an example of a two-dimensional mask for high boost filtering.

The high boost filtering may be modified as shown in Equation 2 below.

High boost = Original + (B) Highpass

It is a method of improving sharpness by proportionally adding a high frequency component multiplied by a weight (B) to the original image.

The peaking filter may be used to divide the integer gray level from the integer gray level. The peaking filter extracts an edge and emphasizes the extracted edge component proportionally to the original image. An example of a method of extracting an edge is using average masking. Average masking is evenly weighted. The picking filter can be obtained through Equation 3 below.

Peaking = (Original) + A (sobel masking)

The peaking filter is shown in FIG.

Through these methods, the gray scale and the gray scale are divided again to improve gray linearity.

However, these filtering methods use filters of the same size. In this case, since the same size of filter is used even when filtering the boundary regions between different objects and objects, resolution may be degraded such as image blurring or image distortion.

6 is for explaining a problem that occurs when filtering is performed using a mask having the same size.

When filtering is performed using a 3 x 3 mask on the cells on the first and second lines of the screen, the filter at the top left is not fully within the area of object 3, which is the background, resulting in image blurring or images. Deterioration of resolution such as distortion occurs.

In addition, when filtering the boundary regions of Object 1 and Object 3, the resolution is reduced because the filter simultaneously filters the region of Object 1 and Object 3. In the case of filtering the boundary areas of the object 2 and the object 3, the resolution decreases because the filter simultaneously filters the area of the object 2 and the object 3.

As described above, when the filtering is performed using the same sized filter, the gray scale power decreases in the boundary region between different objects and objects.

 The present invention is to solve the above problems, to provide an image processing method and an image processing apparatus of the plasma display panel that can minimize the degradation of the resolution between the object and the object when dividing the gray using the filtering. It is for.

In order to achieve the above object, the image processing method and the image processing apparatus of the plasma display panel of the present invention analyze the input gray level signal to classify the object and filter by varying the size of the filter according to the size of the object. do.

The gray scale expression enhancing unit of the present invention is characterized in that it is determined that the boundary of the object when the amount of change of the value calculated by filtering exceeds the reference value in the process of varying the size of the filter.

The gray scale expression enhancing unit of the present invention is characterized in that the size of the filter is changed according to the position of the center pixel in the specific object.

The gray scale expression enhancing unit of the present invention is characterized in that the original gray scale value is used for a cell existing in the boundary region of the image itself.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

7 is a block diagram of an image processing apparatus according to the present invention. As shown in FIG. 7, the image processing apparatus according to the present invention includes a linear scaler 710 and a gray scale expression enhancing unit 720.

The linear scaler 710 converts an 8 bit gray level signal into an n bit gray level signal. The function of the linear scaler 710 is to make it easier to process the gradation signal with a fractional portion by the image processing apparatus of the present invention. At this time, both the 8-bit gray level signal and the n-bit gray level signal are integers. Here, n bits are integer bits larger than 8 bits.

The gradation expression enhancing unit 720 analyzes the input gradation signal, classifies the object, and adjusts the filter size according to the size of the object to perform filtering to convert the integer gradation signal into a gradation signal having a fractional part. That is, n-bit gradation signals are processed and changed to n-bit or more gradation signals.

The gray scale expression enhancing unit 720 may receive a 10-bit gray level signal through the linear scaler 710, but may directly receive an 8-bit image signal. That is, the image processing apparatus according to the present invention may or may not include the linear scaler 710.

8 to 10 are for explaining the operation of the image processing apparatus according to the present invention. As shown in Fig. 8, it is the object 3 (background) of Fig. 6 that is filtered according to the image processing method of the present invention. Mi (i = 1, 1,2,3,, n) is a filter using a mask of i X i, and the gray scale expression enhancing unit 720 changes the size of the filter to fit inside the area of the object. di is the center pixel of the Mi filter.

In this case, the gray scale expression enhancing unit 720 determines that the boundary between the object and the object is determined when the amount of change in the value calculated by the filtering exceeds the reference value, and the object is separated. In addition, the gray scale expression enhancing unit 720 varies the size of the filter applied according to which position of the object the center pixel corresponds to.

For example, if the position of d3 is the cell (3,3) located at the intersection of the third vertical line and the third horizontal line, d3 is the center of the mask, so M3 is a 5 X 5 mask. Therefore, the gray scale expression enhancing unit 720 performs filtering using M3. Next, the resolution enhancer 720 performs filtering using an M3 mask centering on the cells 4 and 3 adjacent to the left side of the cells 3 and 3.

If the filtering calculated value centering on the cells 3 and 3 and the filtering calculated value centering on the cells 4 and 3 are larger than the reference value, the gray scale expression enhancing unit 720 determines the size between the objects and determines the size. Performs filtering using a small filter.

The gray scale expression enhancing unit 720 repeats the above process and performs filtering while varying the filter size for each object region as shown in FIGS. 9 and 10.

In this case, instead of performing filtering on the cells existing in the boundary area of the image itself, the original gray level value is used. For example, in case of a cell existing on a first horizontal line and a second horizontal line, when filtering is performed using an M1 mask having a 3 × 3 centering on cells (1,1), the M1 mask is the left side of FIG. 6. Like the filter located at the top, it exists in the boundary area of the image itself. If filtering is performed in such a boundary area, a problem of deterioration of resolution may occur, so the original gray level value is used as it is.

Such image processing methods and image processing apparatuses are applicable not only in plasma display panels but also in other display apparatuses for displaying digital signals.

As such, those skilled in the art will appreciate that the present invention can be implemented in other specific forms without changing the technical concept or essential characteristics. Therefore, the above-described embodiments are to be understood as illustrative in all respects and not as restrictive.

The scope of the present invention is shown by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. do.

As described above, according to the present invention, the resolution of the object may be prevented by dividing the object from the object and filtering the area of each object by varying the size of the filter.

Claims (9)

An image processing apparatus of a plasma display panel which receives and processes a gray level signal, And an gradation expressing power improving unit configured to classify objects by analyzing the input gradation signals and to filter by varying a filter size according to the size of the object. The method of claim 1, And a linear scaler for increasing a bit of the input gray level signal. The method of claim 1, And the gradation expression improving unit determines that the boundary of the object is greater than the reference value when the amount of change in the value calculated by filtering exceeds the reference value. The method of claim 1, And the gradation representation improving unit changes the size of the filter according to the position of the center pixel in the specific object. The method of claim 1, And the gray scale expression enhancing unit uses the original gray scale value for the cells existing in the boundary region of the image itself. An image processing method of a plasma display panel for receiving a gray level signal and processing the same, And classifying objects by analyzing the input gray level signal and filtering by varying a filter size according to the size of the object. The method of claim 6, And determining the boundary of the object if the amount of change in the value calculated by filtering exceeds a reference value in the process of varying the size of the filter. The method of claim 6, An image processing method of a plasma display panel, the size of a filter being varied according to the position of a center pixel in a specific object. The method of claim 6, An original gray scale value is used for a cell existing in a boundary area of an image itself.

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