KR101666584B1 - Circuit and method for gray-level error control for low power image displays - Google Patents

Abstract

The present invention relates to a method and apparatus for controlling a gradation level error for a low power image display apparatus capable of minimizing power consumption of an image display apparatus while maintaining image quality of a display image at a desired level or higher corresponding to a displayed image, Detecting a reference target value for measuring an image quality of a display image based on a peak signal to noise ratio (PSNR) target; Analyzing image data of red, green, and blue input from outside to generate histograms of red, green, and blue; Analyzing each of the histograms to detect a maximum gradation level of each of red, green, and blue; Detecting an error threshold value by gradually decreasing the level from a highest gradation level among the maximum gradation levels of the detected red, green, and blue colors; Comparing the detected reference target value with an error threshold value; And setting a gray-level clipped point according to the comparison result.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a gray level error control method and apparatus for a low power image display apparatus,

The present invention relates to a method and an apparatus for driving an image display apparatus, and more particularly, to a method and apparatus for driving an image display apparatus that can reduce the power consumption of a video display apparatus while maintaining the image quality of a display image at a desired level or higher, And more particularly, to a method and apparatus for controlling a gradation level error.

Description of the Related Art [0002] In recent years, lightweight thin flat panel displays have been mainly used as image display devices used in monitors for personal computers, portable terminals, and various information devices. As such flat panel display devices, a liquid crystal display, a light emitting display, a plasma display panel, a field emission display, and the like are emerging.

Of the flat panel display devices, the liquid crystal display devices are excellent in resolution, color display, and image quality, and are actively applied to notebook computers, desktop monitors, and mobile terminals.

Such a liquid crystal display device displays an image by adjusting the light transmittance of the liquid crystal using an electric field. To this end, the liquid crystal display device includes a liquid crystal panel having a plurality of liquid crystal cells for displaying an image, a driving circuit for driving the liquid crystal panel, and a backlight unit for irradiating light to the liquid crystal panel.

The liquid crystal panel displays a desired image by adjusting the transmittance of the light emitted from the backlight unit according to the image signal. At this time, the backlight unit drives a plurality of lamps provided in the backlight unit according to the lamp driving control signal supplied from the driving circuit to supply light to the liquid crystal panel.

However, since the backlight unit driven as described above always generates light with a constant brightness irrespective of the image signal of the liquid crystal panel, the power consumption increases. Conventionally, a method has been used in which the brightness of the backlight unit is reduced so as to reduce the power consumption of the backlight unit, and the brightness of the backlight is compensated by changing the light transmittance corresponding to the backlight brightness change rate. However, when the rate of change of brightness of the backlight unit is changed such that it can not be adjusted by changing the light transmittance, a gray level error due to the maintenance of the maximum brightness occurs in the image data exceeding the expressible brightness.

In order to solve this problem, conventionally, the gray level level is saturated with the total gray level number of the image data, and the gray level level clipped rate, which is excluded, is fixed to a specific value, Were applied in advance. However, in the case of the related art, there are problems such as deterioration of the image quality depending on characteristics of specific images that have not been considered in advance, or the brightness of the backlight unit is greatly reduced and the image quality of the image is greatly deteriorated.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and it is an object of the present invention to provide a low-power image display apparatus capable of minimizing the power consumption of a video display device while maintaining the image quality of a display image at a desired level or higher, Level error control method and apparatus.

According to another aspect of the present invention, there is provided a method of controlling a gray level error for a low power image display device, the method comprising: receiving a reference target value for measuring an image quality of a display image based on a peak signal to noise ratio (PSNR) Detecting; Analyzing image data of red, green, and blue input from outside to generate histograms of red, green, and blue; Analyzing each of the histograms to detect a maximum gradation level of each of red, green, and blue; Detecting an error threshold value by gradually decreasing the level from a highest gradation level among the maximum gradation levels of the detected red, green, and blue colors; Comparing the detected reference target value with an error threshold value; And setting a gray-level clipped point according to the comparison result.

The reference target value detection step first detects the PSNR using the following equations,

Using the following equations,

(여기서, λ_r, λ_c, λ_co는 각각 입력 영상의 가로와 세로 화소 수 및 R,G,B 컬러의 수)

(Where, lambda _r , lambda _c , and lambda _co are the number of horizontal and vertical pixels of the input image and the number of R, G, and B colors, respectively)

And the reference target value is calculated.

Wherein the error threshold value detection step includes a step of decreasing the level of the red, green, and blue maximum gradation levels step by step from the largest gradation level of the detected red, green, and blue colors, respectively, , And the red, green, and blue error threshold values are detected using the following equations.

The error threshold value detection step may include detecting the sum of the error threshold values of red, green, and blue, which are detected so that the values are sequentially updated, using the mathematical expression.

According to another aspect of the present invention, there is provided a gradation level error control apparatus for a low power image display apparatus including a target value detector for detecting a reference target value for measuring an image quality of a display image based on a PSNR target, ; A histogram generator for generating red, green, and blue histograms by analyzing red, green, and blue image data input from the outside and analyzing each of the histograms to detect a maximum gradation level of each of red, green, and blue; A red, green, and blue error threshold value detecting unit for detecting the red, green, and blue error threshold values, respectively, by decreasing the level from the highest gray level level among the detected maximum gray level levels, ; An error threshold value detector for summing the error threshold values of the red, green, and blue to detect a final error threshold value; And a comparator for sequentially comparing the detected reference target value with a final error threshold value to set a gradation exclusion point according to the comparison result.

The target value detecting unit first detects the PSNR using the following equations,

Using the following equations,

(여기서, λ_r, λ_c, λ_co는 각각 입력 영상의 가로와 세로 화소 수 및 R,G,B 컬러의 수) 상기 기준 타겟 값을 계산하는 것을 특징으로 한다.

(Where, lambda _r , lambda _c , and lambda _co are the number of horizontal and vertical pixels of the input image and the number of R, G, and B colors, respectively).

Wherein the error threshold value detecting unit detects the error threshold value of each of the red, green, and blue by decreasing the level of the red, green, and blue maximum gradation levels step by step from the largest gradation level of the detected maximum, , And the blue error threshold value is detected using the following equations.

Wherein the error threshold value detector detects the error threshold value of each of the red, green, and blue error threshold values that are sequentially updated to be updated by using an equation.

Wherein the comparator continuously compares the error threshold value with an input threshold value, wherein the error threshold value is sequentially increased with respect to the previously detected reference target value, and when the error threshold value is smaller than the reference target value previously detected, And when the error threshold value is larger than the detected reference target value, sets the previously calculated maximum gradation level to the last gradation exclusion point of the gradation level do.

A method and apparatus for controlling a gray level error for a low power image display apparatus according to an exemplary embodiment of the present invention, which maintains the image quality of a display image at a desired level or higher, corresponding to a displayed image, Can be reduced as much as possible.

1 is a flowchart illustrating a method of controlling a gray level error for a low power image display apparatus according to an exemplary embodiment of the present invention.
2 is a histogram generated according to the gray level values of the red image data.
3 is a histogram generated according to the gray level values of the green image data.
4 is a histogram generated according to the gray level values of the blue image data.
5 is a block diagram showing a gradation level error control apparatus for a low power image display apparatus according to an embodiment of the present invention.
Fig. 6 is a block diagram showing the grayscale exclusion controller shown in Fig. 5 in more detail.

The present invention is described in IEEE Transactions on Consumer Electronics, Vol. 55, No. 4, NOVEMBER 2009 (hereinafter referred to as "Image Integrity-based Gray-Level Error Control for Low Power Liquid Crystal Displays"), which will be hereinafter referred to as a gradation level error control method for a low- And an apparatus will now be described with reference to the accompanying drawings.

FIG. 1 is a flowchart illustrating a gray level error control method for a low power image display apparatus according to an embodiment of the present invention. Referring to FIG.

The gray level error control method shown in FIG. 1 includes the steps of: (T1) detecting a reference target value (TSE _T ) for measuring an image quality of a display image based on a peak signal to noise ratio (PSNR) target; (T2) of analyzing image data (RGB) of red, green and blue inputted from the outside to generate respective histograms of red, green and blue; (T3) analyzing each histogram to detect the maximum gradation level of each of red, green and blue; A step (T4) of detecting an error threshold value (TSE _C ) by gradually decreasing the level from the largest gradation level among the maximum gradation levels of the detected red, green, and blue; (T5) comparing the detected reference target value (TSE _T ) with an error threshold value (TSE _C ); And a step (T6) of setting a gray-level clipped point according to the comparison result.

Based on the detection of the target value as a reference target value (TSE _T) is the reference value for detecting for measuring the quality of the displayed image in PSNR target based on (TSE _T) detection step (T1), based on the target value (TSE _T) In order to do this, we must first detect the underlying PSNR. Here, PSNR can be obtained by using the following equations (1) and (2).

Here, N is the total number of pixels of the input image data, and x _i and y _i are the gradation levels of the input original image data and the i-th pixel of the processed image data, respectively. have.

Since the image data size for one pixel may be 24 bits, each of the red, green, and blue image data is allocated to 8 bits. Thus, the maximum gradation level becomes the 255th gradation level. In addition, when the PSNR is equal to or greater than 30 dB, the target PSNR (target PSNR) of the present invention is set to 30 dB because it is generally acceptable.

The reference target value TSE _T based on the target PSNR and MSE set as described above can be calculated using the following Equations (3) and (4).

Here, λ _r , λ _c , and λ _co may be the number of horizontal and vertical pixels of the input image and the number of R, G, and B colors, respectively.

As described above, in the reference target value (TSE _T ) detection step (T1), the reference target value (TSE _T ) is detected and stored in order to measure the image quality of the display image based on the PSNR target.

Next, in step T2 of generating a histogram, red, green, and blue image data RGB are input to generate histograms of red, green, and blue, respectively. Specifically, as shown in FIGS. 2 to 4, in the histogram generation step T2, tone values of image data (RGB) input from the outside are analyzed in units of one frame, and histograms of red, green, . 2 is a histogram generated according to the gray level values of the red image data, FIG. 3 is a histogram generated according to the gray level values of the green image data, and FIG. 4 is a histogram generated according to the gray level values of the blue image data .

In the step T3 of detecting the maximum gradation level, the respective histograms are analyzed to detect the maximum gradation level I _ccp of each of the red, green and blue colors.

The next step is to set the grayscale exclusion point for generating the converted image data having the PSNR closest to the reference target PSNR of 30 dB or more. This can be applied by varying the ratio of the number of grayscales in which the grayscale level is saturated to the total number of grayscales of the video data, that is, the gray-level clipped rate, .

For this, in the error threshold value (TSE _C ) detection step (T4), the largest gradation level among the maximum gradation levels of red, green and blue detected, for example, the maximum gradation level I _ccp ) to detect the error threshold values (TSE _{R _C} , TSE _{G _C} and TSE _{B _C} ) of each of the red, green and blue. Here, the red, green, and blue error threshold values (TSE _{R - C} , TSE _{G - C} , and TSE _{B - C} ) are detected using the following Equations (5) to (7).

Here, I _{CCP, which} is the maximum gradation level, is a candidate for the maximum gray-level clipped point among the entire gradation levels. If the given maximum gradation level does not satisfy the condition, the calculation is performed by decreasing the gradation level by one gradation level .

Here, I _MAX represents the highest gradation level in each input data of red, green, and blue. The starting point of the maximum gradation level is I _MAX -1 and H _R (i), H _G (i) and H _B (i) are the number of pixels of red, green, .

As described above, the maximum gradation level is detected from the inputted input data of red, green and blue, and the error thresholds (TSE _{R - C} , TSE _{G - C} and TSE _{B - C} ) of red, Green, and blue error thresholds TSE _{R - - C} , TSE _{G - C} , and blue - green threshold values are omitted in a simpler operation by omitting a complicated calculation process of repeatedly comparing respective gradation levels of the conventional input image data, TSE _{B _C} ).

, Red, green, and blue, respectively, of the error threshold value (TSE _{R _C,} TSE _{G _C,} TSE _{B_C)} the error threshold value summation using the equation (8) below, if the detected successively as described above (TSE _C) (T4).

The threshold values TSE _{C that} are summed and detected sequentially increase sequentially corresponding to the respective error threshold values (TSE _{R _C} , TSE _{G _C} , and TSE _{B _C} ) of red, green, and blue whose values are sequentially increased .

In step T5 of comparing the detected reference target value TSE _T with the error threshold value TSE _C , the value is sequentially varied with the reference target value TSE _T previously detected, and the error threshold value TSE _C ). At this time, if the error threshold value TSE _C is smaller than the previously detected reference target value TSE _T , the error threshold value TSE _C is calculated again after decreasing the maximum gradation level by one level.

If the error threshold value TSE _C is greater than the reference target value TSE _T previously detected in the comparison step T5, the previously calculated maximum gradation level is set as the gradation level The final gradation exclusion point is set.

The grayscale exclusion points sequentially detected at least one frame unit through the above-described process are successively supplied to the driving circuit and the backlight control circuit of the image display apparatus and used to set the brightness change rate of the backlight unit and the brightness conversion rate of the image do.

The gray level error control method for a low power image display apparatus according to an exemplary embodiment of the present invention is a method for controlling the gray level level error of the display image in order to minimize the power consumption of the image display apparatus while maintaining the image quality of the display image at a desired level or higher, The gradation exclusion points are set and supplied to the driving circuits of the respective image display devices.

FIG. 5 is a block diagram of a gradation level error control apparatus for a low power image display apparatus according to an embodiment of the present invention. Referring to FIG.

The gradation level error control apparatus shown in Figure 5 is based on a target value of the PSNR target based (TSE _T) and the error threshold (TSE _C) detected by the detected based on the target value of (TSE _T) and the error threshold (TSE _C ), and sets a gradation exclusion point according to a result of the comparison. The image processing apparatus according to claim 1, further comprising: a gradation elimination controller (2) for converting the gradation level of image data A conversion unit 4 and a backlight brightness conversion control unit 6 for controlling the brightness of the backlight unit using the set grayscale exclusion point.

Here, the grayscale elimination controller 2 includes a target value detection unit 21 for detecting a reference target value TSE _T for measuring the image quality of the display image based on the PSNR target, as shown in FIG. 6 attached hereto. A histogram generator for generating histograms of red, green, and blue by analyzing red, green, and blue image data (RGB) input from the outside and analyzing each histogram to detect maximum gray level of each of red, green and blue 22); (TSE _{R _C} , TSE _{G _C} , and TSE _{B _C} ) of each of the red, green, and blue by gradually decreasing the level from the highest gradation level among the maximum gradation levels of the detected red, green, Error threshold detection sections (23, 24, 25) for detecting red, green, and blue, respectively; The red, green, and blue, respectively, of the error threshold value (TSE _{R _C,} TSE _{G _C,} TSE _{B _C)} the error threshold detector (26) for detecting the end of the error threshold value (TSE _C) by summing; And a comparator (27) for sequentially comparing the detected reference target value (TSE _T ) with a final error threshold value (TSE _C ) and setting a gradation exclusion point according to the comparison result.

The target value detection unit 21 detects a reference target value TSE _T for measuring the image quality of the display image based on the PSNR target. In order to detect the reference target value TSE _T , (1) and (2). The reference target value TSE _T based on the target PSNR and the MSE set as described above can be calculated using Equations (3) and (4). As described above, the target value detection unit 21 detects and stores the reference target value TSE _T for measuring the image quality of the display image based on the PSNR target.

As shown in FIGS. 2 to 4, the histogram generator 22 analyzes histograms of image data (RGB) input from the outside in at least one frame to generate histograms of red, green, and blue, respectively. Then, the respective histograms are analyzed to detect the maximum gradation level of each of red, green and blue.

Each of the red, green, and blue error threshold value detectors 23, 24, and 25 reduces the levels of the red, green, and blue maximum gradation levels step by step, And detects each error threshold value (TSE _{R - C} , TSE _{G - C} , TSE _{B - C} ). The above-described red, green, and blue error threshold values (TSE _{R - C} , TSE _{G - C} , and TSE _{B - C} ) are detected using the following Equations (5) to (7), respectively.

Error threshold detector 26, the red, green, and blue, respectively, of the error threshold value (TSE _{R _C,} TSE _{G _C,} TSE _{B _C),} a final error threshold of the summed as shown by the equation (8) ( TSE _C ). The comparing unit 27 sequentially compares the detected reference target value TSE _T with the final error threshold value TSE _C and sets a gray-level clipped point according to the comparison result.

The grayscale exclusion points sequentially detected at least one frame unit through the above-described process are successively supplied to the driving circuit and the backlight control circuit of the image display apparatus and used to set the brightness change rate of the backlight unit and the brightness conversion rate of the image do.

The gray level error control method for a low power image display apparatus according to an exemplary embodiment of the present invention is a method for controlling the gray level level error of the display image in order to minimize the power consumption of the image display apparatus while maintaining the image quality of the display image at a desired level or higher, The gradation exclusion points are set and supplied to the driving circuits of the respective image display devices.

While the present invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. Will be apparent to those of ordinary skill in the art.

2: gray level excluded controller 4: image conversion section
6: backlight brightness conversion control section 21: target value detection section
22: histogram generator 23: red error threshold value detector
24: green error threshold value detector 25: blue error threshold value detector
26: error threshold value detector 27:

Claims (10)

Detecting a reference target value (TSE _T ) for measuring an image quality of a display image based on a peak signal to noise ratio (PSNR) target;
Analyzing image data of red, green, and blue input from outside to generate histograms of red, green, and blue;
Analyzing each of the histograms to detect a maximum gradation level of each of red, green, and blue;
Detecting an error threshold value (TSE _C ) by gradually decreasing the level from the largest gradation level among the maximum gradation levels of the detected red, green, and blue colors;
Comparing the detected reference target value with an error threshold value; And
And setting a gray-level clipped point according to the result of the comparison. The method according to claim 1,
The reference target value detection step
PSNR is first detected using the following equations,

(Where x _i and y _i are the gradation levels of the input original image data and the i-th pixel of the processed image data, respectively)

Using the following equations,

(Where, lambda _r , lambda _c , and lambda _co are the number of horizontal and vertical pixels of the input image and the number of R, G, and B colors, respectively)
A method of controlling a gradation level error for a low power image display apparatus that calculates a reference target value. 3. The method of claim 2,
The error threshold detection step
And a step of detecting the red, green, and blue error threshold values by decreasing the level of the red, green, and blue maximum gradation levels step by step starting with the largest gradation level, Wherein the error threshold value is detected using the following equations.

(Where, H _{R (i),} H _G (i), H _B (i) each of the respective i-th from the gradation level represents the number of red, green and blue input data each pixel, IMAX is a red, green, and blue The highest gradation level in the input data, and I _CCP is the highest gradation level.) The method of claim 3,
The error threshold detection step
And detecting the sum of the error thresholds of the red, green, and blue, each of which is detected so as to be updated in order, by using the following equation: < EMI ID = Control method.

5. The method of claim 4,
The step of comparing the detected reference target value and the error threshold value
Wherein the error threshold value is continuously compared with a reference target value that has been detected in advance and the value is sequentially decreased and an error threshold value to be inputted is continuously compared. When the error threshold value is smaller than the reference target value that was previously detected, the maximum gradation level is decreased by one level Recalculates the error threshold value afterwards,
In the gradation exclusion point setting step
And sets the previously calculated maximum gradation level as a final gradation exclusion point of the gradation level when the error threshold value is larger than the detected reference target value. A target value detector for detecting a reference target value for measuring an image quality of a display image based on a PSNR target;
A histogram generator for generating red, green, and blue histograms by analyzing red, green, and blue image data input from the outside and analyzing each of the histograms to detect a maximum gradation level of each of red, green, and blue;
Green, and blue, respectively, by gradually decreasing the level from the highest gradation level among the maximum gradation levels of the detected red, green, and blue to detect error thresholds (TSEc) of red, green, A threshold value detector;
An error threshold value detector for summing the error threshold values of the red, green, and blue to detect a final error threshold value; And
And a comparator for sequentially comparing the detected reference target value with a final error threshold value to set a gradation exclusion point according to the comparison result. The method according to claim 6,
The target value detector
PSNR is first detected using the following equations,

(Where x _i and y _i are the gradation levels of the input original image data and the i-th pixel of the processed image data, respectively)

Using the following equations,

(Where, lambda _r , lambda _c , and lambda _co are the number of horizontal and vertical pixels of the input image and the number of R, G, and B colors, respectively)
A gradation level error control device for a low power image display device which calculates a reference target value. 8. The method of claim 7,
The error threshold value detector
Green, and blue color thresholds, wherein the red, green, and blue error threshold values are detected by decreasing the levels of the red, green, and blue maximum gradation levels step by step from the largest gray level level, A gradation level error control device for a low power image display device to be detected using the following equations.

(Where, H _{R (i),} H _G (i), H _B (i) each of the respective i-th from the gradation level represents the number of red, green and blue input data each pixel, IMAX is a red, green, and blue The highest gradation level in the input data, and I _CCP is the highest gradation level.) 9. The method of claim 8,
The error threshold value detector
Wherein the error threshold value for each of the red, green, and blue pixels detected to be updated in sequence is detected using the following equation.

10. The method of claim 9,
The comparing unit
Wherein the error threshold value is continuously compared with a reference target value that has been detected in advance and the value is sequentially decreased and an error threshold value to be inputted is continuously compared. When the error threshold value is smaller than the reference target value that was previously detected, the maximum gradation level is decreased by one level Recalculates the error threshold value afterwards,
And sets the previously calculated maximum gradation level as a final gradation exclusion point of the gradation level when the error threshold value is larger than the detected reference target value.

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