KR101867448B1 - Image Processing Method Based on Power Efficient Edge Sharpening - Google Patents

Abstract

The present invention relates to an image processing method based on low-power edge sharpening. An image processing method in the image processing apparatus of the present invention includes a steps of performing high-pass filtering on luminance data separated from color image data to generate high frequency emphasis image data; a step of summing the high-frequency emphasis image data and the luminance data; a step of performing histogram averaging on the summed image data; and a step of combining the result of the histogram averaging and the color difference data of the color image data to generate new color image data. It is possible to obtain a clear image.

Description

[0001] The present invention relates to an image processing method based on low-power edge sharpening,

The present invention relates to an image processing method, and more particularly, to an image processing method for enhancing image clarity by an unsharp masking technique even in a dark screen in a low power system such as a mobile device.

Flat panel displays such as organic light-emitting diodes (OLEDs), plasma display panels (PDPs), and liquid crystal displays (LCDs) have been developed over the past several decades. Such a flat panel display is widely used because it is thinner and lighter than conventional CRT (cathode ray tubes) and provides high linearity and resolution in image quality.

 Flat panel displays, such as LCDs, must be controlled in brightness by the backlight and flat panel displays should be driven in suitably bright conditions to satisfy color quality. However, flat panel displays such as OLED and PDP consume a lot of power and have a problem to solve. Particularly, in the case of a system having a limited power such as a mobile device, a power efficient system is required.

SUMMARY OF THE INVENTION The present invention has been made in order to solve the above-mentioned problems, and it is an object of the present invention to provide a low power system, such as a mobile device, for reconstructing an image in order to obtain an image having improved image clarity, And to provide an image processing method.

According to an aspect of the present invention, there is provided an image processing method in an image processing apparatus for performing high-frequency pass filtering on luminance data separated from color image data, Generating emphasis image data; Summing the high frequency enhanced image data and the luminance data; Performing histogram averaging on the summed image data; And synthesizing the result of histogram averaging and the color difference data of the color image data to generate new color image data.

The step of generating the high frequency emphasis image data may include generating high frequency emphasis image data (y) using a high pass filter and generating corrected high frequency emphasis image data (z) using the following equation ,

Here, the tuning parameters? And? Are real numbers larger than 0 and smaller than 10.

The filter for the high-pass filtering is characterized in that the filtering value H (u, v) for each pixel has a Gaussian characteristic for frequency D _{( u, v )}

Here, Do is the cut-off frequency.

Wherein the summing comprises weighting and summing the high frequency enhanced image data and the luminance data.

According to another aspect of the present invention, there is provided a recording medium embodied by computer readable code, the method comprising: a function of generating high-frequency emphasized image data by performing high-pass filtering on luminance data separated from color image data; A function of summing the high-frequency emphasized image data and the luminance data; A function of performing histogram averaging on the summed image data; And a function of generating new color image data by synthesizing the result of the histogram averaging and the color difference data of the color image data.

In the image processing method according to the present invention, luminance data (Y) filtered using a Butterworth filter-based high-frequency band pass filter even in a low power condition, such as when the screen is dark or dark in a low power system such as a mobile device, By reconstructing the image so that the high frequency portions of the dark image are emphasized on the basis, it is possible to provide an image with improved image sharpness in a power efficient manner.

1 is a flowchart illustrating an image processing method according to an embodiment of the present invention.
2 is an example of a frequency response characteristic of a general Butterworth bandpass filter to which a certain pole-zero is applied.
Figure 3 is an example of images processed according to the tuning parameters [alpha], [beta] of the present invention.
Figure 4 is an example of the original images used in the image processing comparisons of the present invention and existing methods.
Fig. 5 is a comparison result of the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (a).
Fig. 6 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (b).
Fig. 7 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (c).
Fig. 8 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image (d) of Fig.
FIG. 9 shows corresponding images for differences between the present invention and image processing result data by the conventional LPF scheme in a first power saving mode (e.g., factor 5) for the images of FIG.
FIG. 10 shows corresponding images for differences between the present invention and image processing result data by the conventional LPF scheme in a second power saving mode (e.g., factor 10) for the images of FIG.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. In the drawings, the same components are denoted by the same reference symbols as possible. In addition, detailed descriptions of known functions and / or configurations are omitted. The following description will focus on the parts necessary for understanding the operation according to various embodiments, and a description of elements that may obscure the gist of the description will be omitted. Also, some of the elements of the drawings may be exaggerated, omitted, or schematically illustrated. The size of each component does not entirely reflect the actual size, and therefore the contents described herein are not limited by the relative sizes or spacings of the components drawn in the respective drawings.

1 is a flowchart illustrating an image processing method according to an embodiment of the present invention.

The new image processing method according to an embodiment of the present invention can be implemented in a predetermined image processing apparatus, and the image processing apparatus can be implemented by hardware such as a semiconductor processor, software such as an application program, or a combination thereof . The image processing device may be a computing system and may include at least one processor, a memory, a user interface input device, a user interface output device, a storage, and a network interface. A processor may be a central processing unit (CPU) or a semiconductor device that performs processing on instructions stored in memory or storage.

Referring to FIG. 1, in an image processing apparatus according to an exemplary embodiment of the present invention, when a color image data (e.g., R (Red) G (Green) , And converts it into a YCbCr color image (data) composed of luminance data (Y) and color difference data (Cb, Cr) (S20).

For the luminance data Y thus separated from the YCbCr color image, the image processing apparatus emphasizes the high frequency portion by eliminating the DC (direct current) term and uses Butterworth (unsharp masking) effect for the unsharp masking effect Frequency emphasis image data y as shown in Equation (1) (S30) by performing a Butterworth filter-based high-pass filtering. In addition, the high-frequency emphasized image data z can be generated using the tuning parameters alpha (for offset) and beta (for multiplication coefficients) as shown in Equation 2. [ (X = Y) is input data through an image filtering (imfilter) by coefficients h of a high-pass filter based on a Butterworth filter, and the high-frequency emphasis image data y Is generated.

[Equation 1]

&Quot; (2) "

In the present invention, when performing 2D filtering on a predetermined pixel window (e.g., 16 * 16, 32 * 32 pixels, etc.), a high frequency filter (HPF) D _{(u, v)} is larger filter than the frequency cut-off frequency (Do) H (u, v) = filtering of multiplying the first frequency D _{(u, v)} is not more than a frequency cut-off frequency (Do) filtering value H (u , v) = 0. < / RTI >

 &Quot; (3) "

However, in the present invention, a Butterworth filter-based high-pass filter (HPF) is used which calculates a filtering value H (u, v) using an order n as in Equation (4).

&Quot; (4) "

2 is an example of a frequency response characteristic of a general Butterworth bandpass filter to which a certain pole-zero is applied. In FIG. 2, (a) shows the original image, (b) and (c) show the lower cutoff frequency, the higher cutoff frequency, The lower cutoff frequency, the higher cutoff frequency and the order n are (30, 30), (20, 100, 4) 150, 2), (30, 150, 4). It is possible to perform filtering in which the corresponding frequency band between the center low frequency and the surrounding high frequency is appropriately passed. However, the bandpass filter is intended for a predetermined bandpass, but a high-pass filter (HPF) is required for application in a case where the screen is dark in a mobile device and a low-power system as in the present invention.

In the present invention, a predetermined pixel window (for example, 16 * 16, 32 *) is generated using a high pass filter (HPF) having Gaussian function characteristics for frequency without order n as in Equation (5) 32 pixels, etc.) of the pixel data.

&Quot; (5) "

That is, in step S30, the image processing apparatus performs high-pass filtering using a high-pass filter (HPF) having a Gaussian function characteristic as shown in Equation (5) The image data y may be generated and the corrected high frequency enhanced image data z may be generated using Equation 2 using a tuning parameter alpha (e.g., 0.8), beta (e.g., 1.9) .

Figure 3 is an example of images processed according to the tuning parameters [alpha], [beta] of the present invention. (A) is an original image, (b), (c), and (d) are (α, β) = (0.5, 2.0), (0.8, 1.9) . It is desirable that α and β are set to real numbers larger than 0 and smaller than 10, and examples in which (α, β) = (0.8, 1.9) will be described below.

After generating the corrected high-frequency emphasized image data z as in Equation (2), the image processing apparatus compares the luminance data Y in Step S20 with the corrected high-frequency emphasized image of Equation (2) The data z is added up (S40). That is, data (z) in which the high frequency is emphasized is added to the original luminance data (Y), and the data (z) may be weighted and added as required.

Thereafter, the image processing apparatus performs histogram equalization on the summed image data in step S40 (S50). For example, each pixel value of the corresponding image of a predetermined window size may be analyzed, and the corresponding pixel value may be mapped according to a predetermined mapping function in accordance with the frequency occupied by the corresponding image. These techniques are well known and will not be described in detail.

Finally, the image processing apparatus synthesizes the luminance data Y processed in steps S30, S40 and S50 and the chrominance data Cb and Cr in step S20 to generate color image data (for example, R (Red) G ) B (Blue) color data) (S60). (a, b) = (0.8, 1.9), the high-frequency area is emphasized rather than the original image in Fig. 3 (a) Images can be provided. That is, the image can be reconfigured such that the high frequency portions are emphasized even under low power conditions, such as when the screen is dark or when the screen is dark in a mobile device and a low power system, thereby providing an image with improved image clarity in a power efficient manner.

Figure 4 is an example of the original images used in the image processing comparisons of the present invention and existing methods.

Fig. 5 is a comparison result of the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (a). 5, (a) is an image whose brightness is adjusted by a first power saving mode (e.g., factor 5), (b) is an image whose brightness is adjusted by a second power saving mode (E) is a result of the image processing of the present invention with respect to (a), (d) is a result of image processing by the existing LPF (Low Pass Filter) (F) is a result of the image processing according to the present invention with respect to (b). It can be confirmed that the image processing result of the present invention is more improved in image quality than the conventional processing method.

Fig. 6 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (b). 6, (a) is an image whose brightness has been adjusted by a first power saving mode (e.g., factor 5), (b) is an image whose brightness has been adjusted by a second power saving mode (E) is a result of the image processing according to the present invention with respect to (a), (d) is a result of image processing according to the conventional LPF method for (b) The result (f) is the image processing result of the present invention for (b). Here again, it can be seen that the image processing result of the present invention is more improved in image quality than the conventional processing method.

Fig. 7 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image of Fig. 4 (c). 7, (a) is an image in which the brightness is adjusted in a first power saving mode (e.g., factor 5), (b) is an image in which brightness is adjusted in a second power saving mode (E) is a result of the image processing according to the present invention with respect to (a), (d) is a result of image processing according to the conventional LPF method for (b) The result (f) is the image processing result of the present invention for (b). Here again, it can be seen that the image processing result of the present invention is more improved in image quality than the conventional processing method.

Fig. 8 is a result of comparison between the image processing of the present invention and the conventional method with respect to the image (d) of Fig. 8, (a) is an image whose brightness is adjusted by a first power saving mode (e.g., factor 5), (b) is an image whose brightness is adjusted by a second power saving mode (E) is a result of the image processing according to the present invention with respect to (a), (d) is a result of image processing according to the conventional LPF method for (b) The result (f) is the image processing result of the present invention for (b). Here again, it can be seen that the image processing result of the present invention is more improved in image quality than the conventional processing method.

In order to compare the present invention with the image processing by the conventional LPF method, the difference in the image processing results between them is analyzed.

FIG. 9 shows corresponding images for differences between the present invention and image processing result data by the conventional LPF scheme in a first power saving mode (e.g., factor 5) for the images of FIG.

FIG. 10 shows corresponding images for differences between the present invention and image processing result data by the conventional LPF scheme in a second power saving mode (e.g., factor 10) for the images of FIG.

It can be seen that the image difference in the first power saving mode (e.g., factor 5) is more pronounced than in the second power saving mode (e.g., factor 10) of FIG. 10 as in FIG.

As described above, in the image processing method according to the present invention, even when the screen is dark or dark in a low-power system such as a mobile device, the luminance filtered using the Butterworth filter-based high- By reconstructing the image so that the high frequency portions of the dark image are emphasized based on the data Y, it is possible to provide an image with improved image sharpness in a power efficient manner.

The functions for performing the image processing method using weighting using entropy in the image processing apparatus according to an embodiment of the present invention include a computer readable code on a recording medium readable by an apparatus such as a computer, A combination of such a recording medium and a device such as a computer can be implemented to input, output, and display data or information necessary for performing a function. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, a hard disk, a removable storage device, And the like. In addition, the computer-readable recording medium may be distributed in a computer system connected to a network (e.g., the Internet, a mobile communication network, or the like) and may store computer readable codes in a distributed manner and may be executed through a network.

As described above, the present invention has been described with reference to particular embodiments, such as specific elements, and specific embodiments and drawings. However, it should be understood that the present invention is not limited to the above- Those skilled in the art will appreciate that various modifications, additions and substitutions are possible, without departing from the essential characteristics of the invention. Therefore, the spirit of the present invention should not be construed as being limited to the embodiments described, and all technical ideas which are equivalent to or equivalent to the claims of the present invention are included in the scope of the present invention .

Claims (8)

A method of processing an image in an image processing apparatus,
Performing high-pass filtering on luminance data separated from color image data to generate high frequency emphasized image data;
Summing the high frequency enhanced image data and the luminance data;
Performing histogram averaging on the summed image data; And
Synthesizing the result of the histogram averaging and the color difference data of the color image data to generate new color image data,
Wherein the generating the high frequency emphasis image data comprises:
Generating high frequency enhanced image data (y) using a high pass filter and generating corrected high frequency enhanced image data (z) using the following equation,

Wherein the tuning parameters alpha and beta are real numbers greater than zero and less than ten. delete The method according to claim 1,
Wherein the filter for the high-pass filtering comprises:
The filtering value H (u, v) for each pixel has a Gaussian characteristic for frequency D _{( u, v )} according to the following equation,

Wherein Do is a cut-off frequency. The method according to claim 1,
Wherein the summing comprises:
Weighting the high-frequency emphasized image data and the luminance data and summing
The image processing method comprising the steps of: Performing high-pass filtering on luminance data separated from color image data to generate high-frequency emphasized image data;
A function of summing the high-frequency emphasized image data and the luminance data;
A function of performing histogram averaging on the summed image data; And
And a function of generating new color image data by synthesizing the result of the histogram averaging and the color difference data of the color image data,
The function of generating the high-
Generating high-frequency emphasized image data (y) using a high-pass filter, and generating corrected high-frequency emphasized image data (z) using the following equation,

Wherein the tuning parameters alpha and beta are real numbers greater than zero and less than ten. delete 6. The method of claim 5,
Wherein the filter for the high-pass filtering comprises:
The filtering value H (u, v) for each pixel has a Gaussian characteristic for frequency D _{( u, v )} according to the following equation,

Here, Do is a cut-off frequency. 6. The method of claim 5,
The function of summing up,
A function of weighting and summing the high-frequency emphasized image data and the luminance data
And a recording medium.

Images