CN104918029A - Method for enhancing depth of field of image of display - Google Patents

Abstract

The invention discloses a method for enhancing the depth of field of an image of a display. According to the method, the brightness distribution situation of signal input S is put into statistics through a first brightness threshold value B and a second brightness threshold value C, and weighting is performed according to the different brightness of the image. With the method of the invention adopted, when the display is used for dynamic medical image playback, the depth of field and the perspectiveness of the image can be obviously improved under the situation that the backlight brightness of the image is not changed.

Description

Strengthen the method for the display image depth of field

Technical field

The present invention relates to a kind of method strengthening the display image depth of field.

Background technology

Usually when doctor performs an operation, definite observe operative site in order to clear, peep escope to present the enough good depth of field in requiring to adopt, namely can see more content in the same painting face, require that bright the showing slinkingly of display shows that effect difference is obvious.And the method for existing raising display image Deep Canvas is the overall brightness situation by judging image, dynamically adjust backlight illumination, thus reach black more black, bright brighter effect.But the backlight voltage of this method owing to being adjustment, the display situation of integral image can be affected, larger difference is not embodied for the bright dark situation of itself in image, thus not fine for display effect, and along with the continuous movement of endoscope in operation, when run into picture suddenly dimmed or brighten suddenly time, the method can due in adjustment backlight, seeming, picture is in flicker, affects doctor and judges.

Summary of the invention

The present invention seeks to: a kind of method strengthening the display image depth of field is provided.

Technical scheme of the present invention is: a kind of method strengthening the display image depth of field, and it at least comprises:

The first step: provide signal to input S;

Second step: signal is inputted S and be converted to YUV colour gamut signal by RGB colour gamut signal;

3rd step: maximum Max, the minimum M in and the mean value Ave that obtain brightness in pixel, wherein Ave=Count(brightness)/TotalPixel, Count (brightness) is for all luminance weighted, and TotalPixel is pixel number altogether inside piece image;

4th step: the Luminance Distribution situation being carried out statistical signal input S by first and second luminance threshold B, C: when the brightness of signal input S is greater than C, then belong to high-brightness region Z; When signal input S brightness be greater than B and be less than C time, then belong to middle luminance area Y; When the brightness of signal input S is less than B, then belong to low brightness area X, wherein B=(Min+Ave)/2; C=(Max+Ave)/2;

5th step: setting function f (S)=af(x)+bf(y)+cf(z) and carry out grey scale mapping, wherein f(S) and be luminance weighted curve, wherein a, b, c are the weighting parameters of low-light level, intermediate luminance, high brightness, a+b+c=1;

6th step: again YUV colour gamut signal is converted to rgb signal, outputs to display screen.

On the basis of technique scheme, comprise attached technical scheme further:

The reduction formula of described second step is as follows:

$\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]=\left[\begin{array}{ccc}0.257& 0.504& 0.098\\ -0.148& -0.291& 0.439\\ 0.439& -0.368& -0.071\end{array}\right]\×(\left[\begin{array}{c}R\\ G\\ B\end{array}\right]+\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$

The reduction formula of described 6th step is as follows:

$\left[\begin{array}{c}R\\ G\\ B\end{array}\right]=\left[\begin{array}{ccc}1& -0.001& 1.402\\ 1& -0.3441& -0.7141\\ 1& 1.772& 0.001\end{array}\right]\×(\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]-\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$

Advantage of the present invention is:

The present invention, when display is used for dynamic image broadcasting, makes the depth of field of image itself and penetrating sense be significantly improved when by not changing display backlight brightness, be convenient to doctor and use.

Accompanying drawing explanation

Below in conjunction with drawings and Examples, the invention will be further described:

Fig. 1 is flow chart of the present invention;

Fig. 2 is statistics Luminance Distribution situation map of the present invention;

Fig. 3 is dark rank of the present invention curve charts;

Fig. 4 is bright rank of the present invention curve charts.

Embodiment

Embodiment: as shown in Figure 1, it is specific embodiment of the invention method, and it comprises:

The first step: provide signal to input S, signal input S refers to the data inputing to display screen from video card, is preferably octet data;

Second step: signal is inputted S and be converted to YUV colour gamut signal by RGB colour gamut signal, reduction formula is as follows:

$\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]=\left[\begin{array}{ccc}0.257& 0.504& 0.098\\ -0.148& -0.291& 0.439\\ 0.439& -0.368& -0.071\end{array}\right]\×(\left[\begin{array}{c}R\\ G\\ B\end{array}\right]+\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$

3rd step: after converting, the brightness Y of statistics input signal gray-scale intensity distributed areas and each pixel, and obtain maximum Max, minimum M in and the mean value Ave of brightness; Wherein Ave=Count (brightness)/TotalPixel; Wherein Count (brightness)=count (Min)+count (Min+1)+... count (Max), what Count (brightness) was all pixels is luminance weighted, and TotalPixel is pixel number altogether inside piece image; Thus obtain first and second luminance threshold B=(Min+Ave of needs)/2; C=(Max+Ave)/2.

4th step: shown in figure 2, carrys out the Luminance Distribution situation of statistical signal input S: when the brightness of signal input S is greater than C, then belong to high-brightness region Z by first and second luminance threshold B, C; When signal input S brightness be greater than B and be less than C time, then belong to middle luminance area Y; When the brightness of signal input S is less than B, then belong to low brightness area X; Signal input S refers to the 8bit data inputing to display from video card, will dynamically produce the curve of superposition according to being in the pixel number inside luminance area XYZ.Because medical imaging is overall, low-light level part is less usually, intermediate luminance and high brightness composition more, the image namely belonging to Y and Z part is more.

5th step: setting function f (S)=af(x)+bf(y)+cf(z) and carry out grey scale mapping, wherein f(S) be luminance weighted curve, normally when hospital uses, image is made up of the image of high, normal, basic three states, a, b, c is low-light level, intermediate luminance, the weighting parameters of high brightness, a, b, the numerical value of c is the proportions obtained by luma samples, a+b+c=1, a, b, the ratio of c is the low of statistics, in, high brightness number, f (x), f (y), f (z) is the empirical value curve obtained by reference to a large amount of medical image datas.F(x), f(y), f(z) be independent luminance weighted curve (0<x<B, B<y<C, C<z<256), three corresponds respectively to low middle high three kinds of brightness case.Af (x)+bf (y)+cf (z) weighting obtains final dynamic brightness adjustment curve.

Because usual human eye is not linear for the feedback of image, little by little changes under the state on dark rank and just can discover, but larger numerical value change may be needed when bright rank to see.First by general image be dark rank, scala media, these three kinds of situations of bright rank analyze.When arranging dark rank curve f (x), in order to image change can be seen more significantly, dynamically each data of coming in up are improved, as shown in Figure 3, suppose that original curve is straight-through bypass situation, manually draw curve to become arc curve, low gray scale image can be seen clearly.Article 2 is exactly scala media weighted curve f (y), at display itself under the prerequisite of curvature correction, scala media brightness can be done according to the demand of doctor and little by little change, because final depth of field impact is weighted curve f (x) and f (z), thus, weighted curve is directly defaulted as original curve.Luminance weighted curve f (z) of Article 3 is mainly for the high-order ash exponent part in image, as Fig. 4, the situation of relative bypass is by the brightness curve of entirety toward drop-down, and effect, as arc curve, can allow the clear picture of high gray show by dynamically reducing gray scale states like this.

6th step: YUV colour gamut signal is converted to RGB colour gamut signal, and outputs to display screen, wherein reduction formula is as follows:

$\left[\begin{array}{c}R\\ G\\ B\end{array}\right]=\left[\begin{array}{ccc}1& -0.001& 1.402\\ 1& -0.3441& -0.7141\\ 1& 1.772& 0.001\end{array}\right]\&times;(\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]-\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$

The present invention, when display is used for dynamic image broadcasting, makes the depth of field of image itself and penetrating sense be significantly improved when by not changing image back light brightness.

Certain above-described embodiment, only for technical conceive of the present invention and feature are described, its object is to person skilled in the art can be understood content of the present invention and implement according to this, can not limit the scope of the invention with this.All equivalent transformations of doing according to the Spirit Essence of main technical schemes of the present invention or modification, all should be encompassed within protection scope of the present invention.

Claims (3)

1. strengthen a method for the display image depth of field, it is characterized in that it at least comprises:

The first step: provide signal to input S;

Second step: signal is inputted S and be converted to YUV colour gamut signal by RGB colour gamut signal;

3rd step: maximum Max, the minimum M in and the mean value Ave that obtain brightness in pixel, wherein Ave=Count(brightness)/TotalPixel, what Count (brightness) was all pixels is luminance weighted, and TotalPixel is pixel number altogether inside piece image;

4th step: the Luminance Distribution situation being carried out statistical signal input S by first and second luminance threshold B, C: when the brightness of signal input S is greater than C, then belong to high-brightness region Z; When signal input S brightness be greater than B and be less than C time, then belong to middle luminance area Y; When the brightness of signal input S is less than B, then belong to low brightness area X, wherein B=(Min+Ave)/2, C=(Max+Ave)/2;

5th step: setting function f (S)=af(x)+bf(y)+cf(z) and carry out grey scale mapping, wherein f(S) and be luminance weighted curve, wherein a, b, c are the weighting parameters of low-light level, intermediate luminance, high brightness, a+b+c=1;

6th step: again YUV colour gamut signal is converted to rgb signal, outputs to display screen.

2. a kind of method strengthening the display image depth of field as claimed in claim 1, is characterized in that: the reduction formula of described second step is as follows:

$\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]=\left[\begin{array}{ccc}0.257& 0.504& 0.098\\ -0.148& -0.291& 0.439\\ 0.439& -0.368& -0.071\end{array}\right]\&times;(\left[\begin{array}{c}R\\ G\\ B\end{array}\right]+\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$

3. a kind of method strengthening the display image depth of field as claimed in claim 2, is characterized in that: the reduction formula of described 6th step is as follows:

$\left[\begin{array}{c}R\\ G\\ B\end{array}\right]=\left[\begin{array}{ccc}1& -0.001& 1.402\\ 1& -0.3441& -0.7141\\ 1& 1.772& 0.001\end{array}\right]\&times;(\left[\begin{array}{c}Y\\ \mathrm{Cr}\\ \mathrm{Cb}\end{array}\right]-\left[\begin{array}{c}16\\ 128\\ 128\end{array}\right])$