CN103974051A - Image processing apparatus and image processing method - Google Patents

Abstract

The image processing device provided by the invention is used for processing a plurality of first image data of a picture in a first color space. The first color space is defined by a plurality of color elements. The plurality of first color elements do not include a saturation element. The image processing device comprises a conversion module, a gain determination module and an adjustment module. The conversion module is used for converting the plurality of first image data into a plurality of second image data in a second color space. The second color space is defined by a plurality of second color elements. The plurality of second color elements includes the saturation element. The gain determining module is used for determining a saturation gain according to the plurality of second image data and the related part of the saturation element. The adjusting module is used for adjusting the picture according to the saturation gain.

Description

Image processing device and image processing method

technical field

The present invention relates to image processing technologies, and in particular to an image processing device and an image processing method for improving picture saturation.

Background technique

In recent years, with the vigorous development of various electronic products, multimedia systems such as home theaters have become increasingly popular. In most multimedia systems, the most important hardware device is an image display device. How to properly adjust the picture presented by the video display device to meet the preferences of the viewers has always been an important issue concerned by product manufacturers. For example, increasing the sharpness of the image can make the picture clearer, and increasing the saturation of the image can make the color of the picture more vivid.

Existing image processing systems (such as video cameras, digital TVs, DVD players) mostly perform image processing in the YCbCr color space. In other words, if the input signal is image data expressed in RGB color space, the input signal will be converted into image data expressed in YCbCr color space before image processing. As known to those skilled in the art, the three color elements Y, Cb, and Cr defining the YCbCr color space represent lightness, blue chroma, and red chroma, respectively, and saturation is not included. The saturation of a certain image data in the YCbCr color space is expressed by the specific relationship between the two color elements Cb and Cr. Therefore, if you want to analyze the saturation of an image in the YCbCr color space, you must analyze the Cb value and Cr value of each pixel in it. More specifically, it is a two-dimensional analysis of the Cb value and Cr value of each pixel. array for statistics. This analysis program requires a large amount of computing resources (especially when the analysis object is a high-quality video stream), which leads to an increase in the hardware cost of the image processing system. Therefore, almost none of the current image processing systems provides the function of adjusting the saturation of each frame in the dynamic image one by one.

Contents of the invention

In order to solve the above problems, the present invention proposes a new image processing device and image processing method. By converting the image data into a color space whose color elements include a saturation element, it can effectively find Get the saturation information of a picture, and then increase or decrease the saturation of the picture accordingly.

A specific embodiment according to the present invention is an image processing device for processing a plurality of first image data of a frame in a first color space. The first color space is defined by a plurality of first color elements. The image processing device includes a conversion module, a gain determination module and an adjustment module. The converting module is used for converting the multiple pieces of first image data into multiple pieces of second image data in a second color space. The second color space is defined by a plurality of second color elements including a saturation element. The gain determining module is used for determining a saturation gain according to the parts of the plurality of second image data related to the saturation element. The adjustment module is used for adjusting the picture according to the saturation gain.

Another embodiment of the present invention is an image processing method for processing a plurality of pieces of first image data of a frame in a first color space. The first color space is defined by a plurality of first color elements. The image processing method first executes a conversion step, converting the multiple pieces of first image data into multiple pieces of second image data in a second color space. The second color space is defined by a plurality of second color elements. The plurality of second color elements include a saturation element. Next, the image processing method executes a determining step of determining a saturation gain according to the portions of the plurality of second image data related to the saturation element. The image processing method then performs an adjustment step to adjust the image according to the saturation gain.

Description of drawings

In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

FIG. 1 is a functional block diagram of an image processing device according to an embodiment of the present invention.

2A-2C are used to present several examples of objects that can be adjusted by the adjustment module according to the present invention.

FIG. 3 is a functional block diagram of an image processing method according to an embodiment of the invention.

Figure 4 is an example of a saturation histogram.

100: image processing device 12: conversion module

14: Gain determination module 16: Adjustment module

S31~S33: process steps

Detailed ways

An embodiment of the present invention is an image processing device, the functional block diagram of which is shown in FIG. 1 . The image processing device 100 includes a conversion module 12 , a gain determination module 14 and an adjustment module 16 . In practical applications, the image processing device 100 can be integrated in various electronic systems that require adjusting image saturation, or can exist independently.

The conversion module 12 is responsible for converting image data between different color spaces. In this embodiment, a first color space is defined by a plurality of first color elements, and the plurality of first color elements do not include a saturation element. In contrast, a second color space is defined by a plurality of second color elements, and the plurality of second color elements include saturation elements. In one embodiment, the first color space may be RGB color space or YCbCr color space, and the second color space may be HSV color space, HSL color space or HIS color space. The following embodiments are mainly illustrated by taking the first color space as an RGB color space and the second color space as an HSV color space as an example, but the scope of the present invention is not limited thereto.

In this embodiment, the input signal of the conversion module 12 is a frame of multiple image data in the RGB color space (hereinafter referred to as RGB image data). In practice, a video stream provided to the image processing device 100 may include a plurality of frames, including the frame input to the conversion module 12, and the image processing device 100 can respectively perform image processing on the multiple frames included in the video stream. handler. The conversion module 12 converts these RGB image data into a plurality of image data (hereinafter referred to as HSV image data) in the HSV color space of the frame according to the following equation:

H=max(R,G,B)-min(R,G,B),

V=max(R,G,B),

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; if\; H</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ \frac{\mathrm{<span\; class="notranslate">\; h</span>}}{\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; if\; H</span>}<span\; class="notranslate">\; \&NotEqual;</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.<span\; class="notranslate">\; .</span>$

The three color elements H, S, and V that define the HSV color space represent hue, saturation, and luminance, respectively. That is to say, the output signal of the conversion module 12 includes the saturation information of each piece of image data.

Subsequently, the gain determining module 14 determines a saturation gain according to the part related to the saturation element S in the HSV image data provided by the conversion module 12 . In one embodiment, the gain determination module 14 creates a saturation histogram of the HSV image data, the horizontal axis represents the saturation, and the vertical axis represents the number of pixels with a certain saturation in the frame. In the saturation histogram example shown in FIG. 4 , the normalized saturation distribution ranges from 1 to 32, and the saturation value corresponding to the largest number of pixels in the histogram is 28. In one embodiment, the gain determining module 14 may directly select 28 as the representative saturation of the frame. In another embodiment, the gain determination module 14 may accumulate the pixel quantities corresponding to different saturations starting from the part with the lowest saturation, and find out that a ratio of the accumulation result to the total pixel quantity is higher than a threshold value (for example, one hundred The saturation corresponding to ninety-five minutes) is used as the representative saturation of the picture.

In practice, there are many ways to calculate the saturation gain. In one embodiment, the saturation gain is set as the calculation of dividing the saturation upper limit by the representative saturation (in the aforementioned embodiment, ie 32 divided by 28) Consequently, in another embodiment, the saturation gain is set as the calculated result of multiplying the representative saturation by a specific weight (for example, multiplying 28 by 1.05 or 0.95). The specific proportion can be selected according to the user's preference, and can also be a fixed value preset before the product leaves the factory.

It is worth noting that no matter what the method of generating the saturation gain is, since the HSV image data provided to the gain determination module 14 directly contains the saturation information of each pixel, the gain determination module 14 can find Display the representative saturation of a frame. In other words, as long as the definition of the color space corresponding to the output signal of the conversion module 12 includes a saturation element, the gain determination module 14 can quickly and effectively find out the saturation information of the image. In addition, it should be noted that different users have different visual perceptions, and there is usually no optimal standard for image saturation. Therefore, the gain determining module 14 can determine which method should be used to determine the saturation gain according to empirical rules.

Next, the adjustment module 16 is responsible for adjusting the image according to the saturation gain generated by the gain determination module 14 . In practice, the objects to be adjusted by the adjustment module 16 can be determined according to backend requirements. In one embodiment, as shown in FIG. 2A , the adjustment module 16 can directly change the RGB image data of the frame according to the saturation gain, for example, multiply the RGB image data by the saturation gain respectively. In another embodiment, as shown in FIG. 2B , the adjustment module 16 can change the HSV image data of the frame according to the saturation gain, for example, multiply each saturation element S in the HSV image data by the saturation gain . If the format of the output signal that the image processing device 100 needs to provide to the back-end circuit is RGB data, the changed HSV image data can be converted back to RGB image data again.

In another embodiment, as shown in FIG. 2C, the conversion module 12 also converts the RGB image data of one frame into multiple third image data in another third color space (such as YCbCr color space), and the adjustment module Step 16 is to multiply the plurality of third image data by the saturation gain according to the saturation gain, so as to achieve the effect of adjusting the image. If the third color space is the YCbCr color space, the adjustment module 16 can multiply the Cb value and Cr value of each piece of image data by the saturation gain without adjusting the Y value. The advantage of this method is that the brightness of the picture will not be affected by the change of saturation.

In practice, the adjustment module 16 can directly use the saturation gain provided by the gain determination module 14 as the product for adjusting each image data, or find out the product corresponding to the saturation gain according to a lookup table or a specific calculation formula to adjust the image data .

Another embodiment of the present invention is an image processing method, the flowchart of which is shown in FIG. 3 . The image processing method is used for processing a plurality of first image data of a frame in a first color space. The first color space is defined by a plurality of first color elements that do not include a saturation element. The second color space is defined by a plurality of second color elements including the saturation element. The image processing method first executes step S31 to convert the multiple pieces of first image data into multiple pieces of second image data in a second color space. Next, the image processing method executes step S32 to determine a saturation gain according to the parts of the plurality of second image data related to the saturation element. The image processing method then executes step S33 to adjust the image according to the saturation gain.

The various circuit operation changes (such as the way of determining the saturation gain) described in the introduction of the image processing device 100 can also be applied to the image processing method shown in FIG. 3 , and the details will not be repeated here.

As mentioned above, the present invention proposes a new image processing device and image processing method. By converting the image data into a color space whose color elements include a saturation element, it can effectively find Saturation information of a picture, and then increase or decrease the saturation of the picture accordingly. The device and method according to the present invention can be applied in various electronic systems (such as video cameras, digital TVs, DVD players) that need to adjust image saturation, and its application scope includes dynamic images and still images.

Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make some modifications and improvements without departing from the spirit and scope of the present invention. Therefore, the present invention The scope of protection should be defined by the claims.

Claims (20)

1. An image processing device for processing a plurality of first image data of a frame in a first color space, where the first color space is defined by a plurality of first color elements, the image processing device comprising: A conversion module, used to convert the multiple pieces of first image data into multiple pieces of second image data in a second color space, the second color space is defined by multiple second color elements, the multiple second The color element contains a saturation element; a gain determination module, used to determine a saturation gain according to the parts of the plurality of second image data related to the saturation element; and An adjustment module is used for adjusting the picture according to the saturation gain. 2. The image processing device according to claim 1, wherein the first color space is an RGB color space or a YCbCr color space. 3. The image processing device according to claim 1, wherein the second color space is an HSV color space, an HSL color space or a HIS color space. 4. The image processing device according to claim 1, wherein the gain determination module makes a saturation histogram of the multiple pieces of second image data to find a representative saturation of the frame, and according to the Representative Saturation determines the Saturation Gain. 5. The image processing device according to claim 4, wherein the plurality of second image data corresponds to a total number of pixels, and the gain determination module is from a lowest saturation to a highest saturation of the saturation histogram Accumulate a number of pixels, and when the ratio of the number of pixels to the total number of pixels is higher than a threshold value, the gain determination module uses the saturation corresponding to the number of pixels as the representative saturation. 6 . The image processing device according to claim 1 , wherein the adjustment module multiplies the plurality of first image data by the saturation gain to adjust the image. 7 . The image processing device according to claim 1 , wherein the adjustment module multiplies the saturation elements of the plurality of second image data by the saturation gain to adjust the image. 8. The image processing device according to claim 1, wherein the conversion module further converts the plurality of first image data into a plurality of third image data in a third color space, and the adjustment module converts The plurality of third image data are respectively multiplied by the saturation gain to adjust the image. 9. The image processing device according to claim 8, wherein the first color space is an RGB color space, the second color space is an HSV color space, and the third color space is a YCbCr color space, And the adjustment module multiplies the respective Cb values and Cr values of the plurality of third image data by the saturation gain to adjust the image. 10. The image processing device of claim 1, wherein the frame is included in a video stream provided to the image processing device, and the image processing device adjusts a plurality of frames included in the video stream. 11. An image processing method for processing a plurality of first image data of a frame in a first color space, where the first color space is defined by a plurality of first color elements, the image processing method comprising: (a) converting the plurality of first image data into a plurality of second image data in a second color space, the second color space is defined by a plurality of second color elements, and the plurality of second color elements include a saturation element; (b) determining a saturation gain according to the parts of the plurality of second image data related to the saturation element; and (c) Adjust the picture according to the saturation gain. 12. The image processing method according to claim 11, wherein the first color space is an RGB color space or a YCbCr color space. 13. The image processing method according to claim 11, wherein the second color space is an HSV color space, an HSL color space or a HIS color space. 14. The image processing method according to claim 11, wherein step (b) comprises: (b1) making a saturation histogram of the multiple pieces of second image data to find a representative saturation of the frame; and (b2) Determine the saturation gain based on the representative saturation. 15. The image processing method according to claim 14, wherein the plurality of second image data corresponds to a total number of pixels, and the step (b1) includes: accumulating a number of pixels from a lowest saturation to a highest saturation of the saturation histogram; and When a ratio of the accumulated pixel quantity to the total pixel quantity is higher than a threshold value, the saturation corresponding to the pixel quantity is used as the representative saturation. 16. The image processing method according to claim 11, wherein step (c) comprises multiplying the plurality of pieces of first image data by the saturation gain to adjust the image. 17. The image processing method according to claim 11, wherein the step (c) comprises multiplying the saturation elements of the plurality of second image data by the saturation gain to adjust the image. 18. The image processing method as claimed in claim 11, further comprising: converting the multiple pieces of first image data into multiple pieces of third image data in a third color space; The step (c) includes multiplying the plurality of third image data by the saturation gain to adjust the image. 19. The image processing method according to claim 18, wherein the first color space is an RGB color space, the second color space is an HSV color space, and the third color space is a YCbCr color space, And the step (c) includes multiplying the respective Cb values and Cr values of the plurality of third image data by the saturation gain to adjust the image. 20. The image processing method of claim 11, wherein the frame is included in a video stream, and the image processing method is used to adjust a plurality of frames included in the video stream.