CN101651845A - Method for testing definition of moving images of display devices - Google Patents

Abstract

The invention provides a method for testing definition of moving images of display devices, comprising the following steps: A: using a high speed camera to continuously shoot and record moving test strips of display elements or the display devices; B: carrying out moving tracking pretreatment, aligning the images of a plurality of continuous frames in a mode of unchanging relative position or alignment moving centre according to the moving tracking effect of human vision, and taking out brightness and chroma data of pixel coordinates with unchanging relative positions; C: carrying out time-domain filtering on the taken brightness and chroma data of the pixel coordinates with unchanging relative positions; and D: selecting a test image after time-domain filtering, taking out the brightnessand chroma data of the pixel of the domain to be analyzed, and carrying out spatial domain filtering. The test method considers time-domain characteristics and spatial domain characteristics of humaneyes simultaneously, the test result is more accurate, and the problem that evaluation parameters of definition for the moving images and static images are inconsistent is solved.

Description

A kind of method for testing definition of moving images of display devices

Technical field

The present invention relates to the definition of moving images technical field of measurement and test, particularly a kind of method for testing definition of moving images of display devices.

Background technology

TV industry carries out the transition to high definition digital television from traditional analog television has become inevitable trend, flat panel display field product makes rapid progress in recent years, for example rear-projection TV, LCD (LCD), plasma television (PDP), digital light projection TV (DLP), organic photoelectric display (OLED) etc.Because physics realization mechanism and type of drive is different, and a great difference is arranged on moving image quality.The consumer not only requires outstanding static definition, and requires display device that good moving image display capabilities is arranged.Show that relevant industries need the definition of moving images measuring technology.Have some measuring technologies at present both at home and abroad:

(1) subjective testing method

Measuring signal generator sends definition of moving images striped test signal, and the response time test signal of perhaps trailing by the subjective discrimination threshold of human eye, is read the definition of moving images tv line, parameters such as the response time of perhaps trailing.But the problem that this method exists is: relying on subjective testing, is not a kind of objective examination method, and testing efficiency is not high, and precision is limited, therefore is difficult to use at plant produced line and research institute.

(2) follow the tracks of the camera method

This method design philosophy is based on the motion tracking effect of eyeball, and when promptly eye-observation was to the low-speed motion object, eyeball can be followed the trail of this moving object, and constantly focuses on clear to observe.Therefore if measure dynamic definition, two behaviors of tracking and focusing that just must the emulation human eye.Its technical scheme adopts feed back control system to handle video camera tracking image position, regulates video camera simultaneously automatically and focuses on.Do not require high-speed camera, the time for exposure is larger than a refresh time.Specific implementation has rotation to follow the tracks of and two kinds of methods of linear tracking.On algorithm, the spatial distribution of test pattern is carried out filtering with human eye contrast sensitivity function (CSF), obtain discernable obscurity boundary width (PEBW) at last, and with the evaluating index of discernable obscurity boundary width (PEBW) as definition of moving images.

But there is following problem in this method:

(2.1) with discernable obscurity boundary width (PEBW) as evaluating, lack contact with " tv line " of static definition, be difficult to static definition of comparison and dynamic definition;

(2.2) system realizes relying on high precision tracking and autofocus system, and difficulty is very big, and cost is too high;

What (2.3) human visual system's simulation algorithm of this method of testing adopted is human eye contrast sensitivity function (CSF) model, and this model has only been considered the spatial character of human eye vision, does not consider time response, therefore comprehensive inadequately to human visual system's emulation.Human eye contrast sensitivity function (CSF) model is meant when human eye is watched the black and white strip of spatial distribution, the relation between fringe contrast that subjective feeling arrives and the striped spatial distribution frequency.Subjective test shows, human eye is very responsive to the black and white strip of a certain frequency, along with the frequency of black and white strip is higher or lower than this sensitive frequency, the human eye subjective feeling to contrast descend gradually, therefore this model belongs to the spatial character of human eye vision, does not consider time response.

(3) high speed camera method (High Speed Camera)

This method need not be followed the tracks of camera, and the image change recording occurring continuously in is got off with high speed camera, for example with 8-10 high speed camera frame under the moving image record of display in one, use " integration " algorithm to handle then: according to the constant principle aligned frame position of relative position, persist principle according to human eye vision then, the brightness data at the constant place of relative position of the high speed camera frame in is carried out asking average behind the integration, obtain discernable obscurity boundary width (PEBW) at last, and with the evaluating index of discernable obscurity boundary width (PEBW) as definition of moving images.

But there is following problem in this method:

(3.1) with discernable obscurity boundary width (PEBW) as evaluating, lack contact with " tv line " of static definition, be difficult to static definition of comparison and dynamic definition;

What (3.2) human visual system's simulation algorithm of this method of testing adopted is " integration " algorithm, and this model has only been considered the time response of human eye vision, does not consider spatial character, and is therefore comprehensive inadequately to human visual system's emulation.And " integration " algorithm is also not accurate enough to the time response emulation of human eye vision, and its theoretical foundation is " human eye vision persists " phenomenon.But the essence of this phenomenon is the time domain frequency response of human eye, is not integrating effect, so also there is certain problem in this algorithm.

(4) the moving image response time (Motion Picture Response Time)

This method is a parameter with the moving image response time (MPRT) of display, can test the moving image response time (MPRT) when different gray scale variation.Technology realizes adopting the square that glimmers between the different gray scale ladders in the some cycles as resolution chart, adopt Photometer for Flashing Light to measure the brightness response curve of TV, calculate the transient state ladder response time thus, and, further calculate discernable obscurity boundary width (PEBW) by simulation algorithm.

But there is following problem in this method:

(4.1) (MPRT) is time quantum the evaluating moving image response time, though can be converted into discernable obscurity boundary width (PEBW) through certain algorithm, but the conversion process will inevitably be introduced error, and still lack contact with " tv line " of static definition, be difficult to static definition of comparison and dynamic definition;

(4.2) Photometer for Flashing Light test is the mean value of a brightness zone in, can not emulation or " motion tracking " characteristic of compensation human eye, so test result lacks and the getting in touch of subjective assessment result.

In a word, existing various method of testings exist following two problems:

(1) human visual system's model is perfect inadequately.What human visual system's simulation algorithm of existing tracking camera method of testing adopted is human eye contrast sensitivity function (CSF) model, and this model has only been considered the spatial character of human eye vision, does not consider time response.And human visual system's simulation algorithm of high speed camera method of testing adopts is " integration " algorithm, and this model has only been considered the time response of human eye vision, does not consider spatial character.And " integration " algorithm is also not accurate enough to the time response emulation of human eye vision, and its theoretical foundation is " human eye vision persists " phenomenon.But the essence of this phenomenon is the time domain frequency response of human eye, is not integrating effect, so also there is certain problem in this algorithm to the emulation of human eye time domain specification.

(2) definition of moving images evaluating and still image definition evaluating are inconsistent.Existing tracking camera method of testing and high speed camera method of testing all adopt the evaluating index of discernable obscurity boundary width (PEBW) as definition of moving images, inconsistent with still image definition parameter, be difficult between moving image and still image definition, compare.

Summary of the invention

The objective of the invention is to, a kind of method for testing definition of moving images of display devices is provided, can consider the time domain characteristic and the spatial domain characteristic of human eye simultaneously, test result is more accurate; And, solved moving image and the inconsistent problem of still image definition evaluating.

Method for testing definition of moving images of display devices of the present invention comprises the following steps:

Steps A: the exercise test striped of display device or display device is taken and noted to high speed camera continuously;

Step B: carry out the motion tracking preliminary treatment, motion tracking effect according to human eye vision, the image of a plurality of successive frames is constant or align in the mode of centre of motion alignment according to relative position, and take out the brightness and the chroma data of the constant pixel coordinate of relative position;

Step C: the brightness and the chroma data of the pixel coordinate that the relative position of described taking-up is constant carry out time-domain filtering;

Step D: choose the width of cloth test picture behind the time-domain filtering, take out the brightness and the chroma data of the pixel in zone to be analyzed, carry out spatial domain filtering.

Wherein, before described steps A, further comprise the following steps:

Produce chequered with black and white test striped certain movement speed, that fringe spacing and thickness do not wait by flying-spot video generator, and drive tested display device and correctly show this moving image.

Wherein, in described step C, described time-domain filtering is the processing method that adopts low pass filter filtering; Described spatial domain filtering is the processing method that adopts band-pass filter.

In addition, may further include step e: judge according to the modulation degree threshold values whether certain tv line can be discerned by subjectivity.

Wherein, described modulation degree M is meant the ratio of luminance difference with the black and white strip brightness sum of black and white strip, the modulation degree threshold values of certain tv line correspondence of process filtering processed images is greater than 5%, think that then this tv line can be identified, otherwise can not be identified, can discern and unrecognizable boundary position, be exactly the tv line of the definition of moving images under this movement velocity.

Wherein, described step e comprises the following steps:

Step e 1: brightness and the chroma data of described step D being handled a certain tv line in the image of back take out, and form array R ₂(0, j);

Step e 2: find all maximum points and the minimum point of tv line to be analyzed,, m minimum and n maximum should be arranged then if test pattern alternately is made of m black streaking and n informal voucher line with the brightness of position distribution;

Step e 3: according to the brightness data of these maximum value minimum points, calculate modulation degree, should have m, get worst-case value in these modulation degree as the modulation degree of this tv line to n modulation degree by the described formula of preamble;

Step e 4: repeating step E1 calculates the modulation degree of all sampling points that need test to step e 3.Sampling is according to certain analysis spacing;

Step e 5: finding modulation degree near 5% tv line, is exactly result of calculation.

Wherein, the modulation degree of rest image is: ${\mathrm{<figure-callout\; id="0"\; label="M"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">M</figure-callout>}}_0=\frac{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^0-{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^0)}{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^0+{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^0)},$ The modulation degree of moving image is: ${\mathrm{<figure-callout\; id="0"\; label="M"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">M</figure-callout>}}_0=\frac{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^1-V_0^1)}{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^1+V_0^1)},$ Wherein, V ₀ ⁰Brightness value for the black streaking correspondence in the static resolution chart; V ₁ ⁰Brightness value for the informal voucher line correspondence in the static resolution chart; V ₀ ¹Brightness value for the black streaking correspondence among the exercise test figure; V ₁ ¹Brightness value for the informal voucher line correspondence among the exercise test figure.

Wherein, the evaluating of definition of moving images measurement result is the evaluating that can directly compare with the still image definition, comprises in " line ", " line to ", " line right/screen size " or " tv line " at least a.

Wherein, when the test striped was static, the brightness of the pixel in zone to be analyzed on this direction of motion changed by sinusoidal wave distribution:

$G\left(j\right)=\frac{1}{2}(1+\cos (2\mathrm{\&pi;}\&CenterDot;\frac{{\mathrm{<figure-callout\; id="0"\; label="W\; L\; W"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">W</figure-callout>}}_L}{W_{}}\&CenterDot;j))\&CenterDot;255$

Wherein, G (j) is this direction of motion of screen upper edge, in the brightness number of j the pixel in zone to be analyzed; W ₀It is this direction physical resolution; W _LIt is the tv line of this black and white strip correspondence; When the test striped moves with v pixel/field, if the brightness of the pixel of position j is G (j) certain the time, then next the time, the brightness of position j+v place pixel also is G (j).

The invention has the beneficial effects as follows: according to method for testing definition of moving images of display devices of the present invention, a kind of model of human visual system more accurately is provided, this model has been considered the time domain characteristic and the spatial domain characteristic of human eye simultaneously, and " time-domain filtering " algorithm replaces existing " integration " algorithm with more accurately; In addition, the definition of moving images evaluating and the inconsistent problem of still image definition evaluating of existing method of testing, the present invention adopts " modulation degree " thresholding algorithm to obtain the dynamic image definition, with " tv line " is parameter, consistent with still image definition parameter, can between moving image and still image definition, compare.

Description of drawings

Fig. 1 schematic diagram of territory frequency response at the moment of behaving;

Fig. 2 is a human eye spatial domain frequency response schematic diagram;

Fig. 3 is human visual system's simulation algorithm comparison result schematic diagram of LCD TV;

Fig. 4 is human visual system's simulation algorithm comparison result schematic diagram of plasm TV;

Fig. 5 is definition (right side) schematic diagram of definition of moving images test striped (left side) and modulation degree;

Fig. 6 is the horizontal direction Luminance Distribution schematic diagram of certain LCD TV 720 tv line;

Fig. 7 is the horizontal direction Luminance Distribution schematic diagram of certain LCD TV 700 tv line;

Fig. 8 is the comparison result schematic diagram of LCD TV subjective assessment result and modulation degree algorithm;

Fig. 9 is the comparison result schematic diagram of plasm TV subjective assessment result and modulation degree algorithm.

Embodiment

Below, 1～9 describe method for testing definition of moving images of display devices of the present invention in detail with reference to the accompanying drawings.

Method for testing definition of moving images of display devices of the present invention comprises the following steps:

Step 1: video test sequence takes place.Flying-spot video generator produce certain movement speed, fringe spacing and thickness do not wait, and also is the chequered with black and white test striped that the definition television line does not wait, and drive tested display device and correctly show this moving image.

Step 2: high speed camera is taken and record continuously.Take the moving image that shows with high speed camera, and note.

Step 3: " motion tracking " preliminary treatment.According to " motion tracking " effect of human eye vision, the image of several successive frames (for example 64) mode constant according to relative position or centre of motion alignment is alignd, and take out the brightness and the chroma data of the constant pixel coordinate of relative position.

Wherein, in step 3, if testing level direction definition of moving images, to China's high-definition television standard, W ₀Be 1920.W _LCan get tv lines such as 700,720,740.

Step 4: the time-domain filtering part in the correction of human visual system's model.The brightness and the chroma data of the pixel coordinate that the relative position of taking-up is constant carry out time-domain filtering.

Step 5: the spatial domain filtering part in the correction of human visual system's model.Choose the width of cloth test picture behind the time-domain filtering, take out the brightness and the chroma data of the pixel in zone to be analyzed, carry out spatial domain filtering.

Step 6: threshold modulation is calculated tv line.Each definition striped of the revised image of human visual system's model is calculated modulation degree, and the tv line that reaches threshold modulation is exactly the definition of moving images test result, and parameter is " tv line ".

Wherein, step 3 to step 5 has constituted human visual system's model emulation algorithm of the present invention, and promptly this algorithm is made of three parts: preliminary treatment, time-domain filtering and airspace filter.The execution sequence of this three part has constituted two kinds of embodiments of this algorithm.An embodiment is to carry out according to the order of preliminary treatment, time-domain filtering and airspace filter; Another embodiment is to carry out according to the order of preliminary treatment, airspace filter and time-domain filtering.

Below, introduce the embodiment of carrying out according to the order of preliminary treatment, time-domain filtering and airspace filter in detail:

Step 31: preliminary treatment.

Need data are carried out preliminary treatment before the time-domain filtering algorithm, " motion tracking " effect according to human eye vision, the image of several successive frames (for example 64) need be alignd at mode constant according to relative position or centre of motion alignment, and take out the brightness and the chroma data of the constant pixel coordinate of relative position, these data are formed array.

For example the brightness value of the pixel to be analyzed of first frame in the successive frame is that (x, y), x, y be horizontal coordinate and the vertical coordinate in the remarked pixel image respectively for r.The movement velocity of picture centre is v pixel/high speed camera frame, horizontal motion, and just the every frame of the central point of these high speed camera successive frames moves the v pixel to a direction.Consider convenience of calculation, v can be rounded.With the brightness data at the relative location of pixels invariant point place of these successive frames form array R (i, j), the situation when for example getting 64 analysis frames:

R (0, j)=(x, y), (x y) is first width of cloth figure to r0 to r0.

R (1, j)=(x, y+v), (x y+v) is second width of cloth figure to r1 to r1.

R (2, j)=(x, y+2*v), (x y+2*v) is the 3rd width of cloth figure to r2 to r2.

R (3, j)=(x, y+3*v), (x y+3*v) is the 4th width of cloth figure to r3 to r3.

R (63, j)=(x, y+63*v), (x y+63*v) is the 64th width of cloth figure to r64 to r64.

Step 32: time-domain filtering.

Only consider the test of horizontal motion image definition, the array R after the preliminary treatment (i j) carries out time-domain filtering according to following formula, and two kinds of embodiments of time domain and frequency domain can be arranged:

Time frequency domain embodiment: earlier with pixel data by being fourier transformed into frequency domain, multiply by filter function, and then Fourier inversion returns time domain, obtain behind the time-domain filtering array of pixels R1 (i, j).

R ₁(i，j)＝F ^-1(F(R(i，j))·T(j))

F is a Fourier transform in the following formula, F ^-1Be Fourier inversion, T is the time-domain filtering function.

The time domain embodiment: with pixel data and time-domain filtering convolution of functions, directly filtering.

$R_1(i,j)=R(i,j)\&CircleTimes;W\left(j\right)$

W is the time-domain filtering function in the following formula.

Step 33: airspace filter.

Get time-domain filtering piece image afterwards and carry out airspace filter, the array R1 after for example selected time-domain filtering (0, j) carry out airspace filter according to following formula, two kinds of embodiments of spatial domain and spatial frequency domain can be arranged:

The spatial frequency domain embodiment: earlier with pixel data by being fourier transformed into frequency domain, multiply by filter function, and then the Fourier inversion territory of making the return trip empty, obtain behind the airspace filter array of pixels R2 (0, j).

R ₂(0，j)＝F ^-1(F(R ₁(0，j))·S(j))

F is a Fourier transform in the following formula, F ^-1Be Fourier inversion, S is the airspace filter function.

The spatial domain embodiment: with pixel data and airspace filter convolution of functions, directly filtering.

$R_2(0,j)=R_1(0,j)\&CircleTimes;P\left(j\right)$

P is the airspace filter function in the following formula.

In addition, in above-mentioned steps 6, threshold modulation is calculated tv line, and concrete execution in step is as follows:

Step 61: the brightness and the chroma data of a certain tv line in the image after human visual system's models treated (for example 700 lines) are taken out, form array R ₂(0, j).

Step 62: find all maximum points and the minimum point of tv line to be analyzed with the brightness of position distribution.If test pattern alternately is made of m black streaking and n informal voucher line, m minimum and n maximum should be arranged then.

Step 63: according to the brightness data of these maximum value minimum points, calculate modulation degree, should have m, get worst-case value in these modulation degree as the modulation degree of this tv line to n modulation degree by the described formula of preamble.

Step 64: repeating step 61 calculates the modulation degree of all sampling points that need test to step 63.Sampling is according to certain analysis spacing (for example 700,720,740 tv lines).

Step 65: finding modulation degree near 5% tv line, is exactly result of calculation.

Method for testing definition of moving images of display devices of the present invention is realized by human visual system's model emulation algorithm with based on " tv line " computational methods of dispatching threshold values by video generator, high speed camera.

After flying-spot video generator is sent test signal into TV to be measured, will show the resolution pattern of motion on the TV, vision signal takes place to produce the moving image of 0-6 pixel/field.At this moment can carry out continuous shooting and note the picture of shooting results with high speed camera.The high speed camera shooting speed was 500 frame/seconds, the RGB color mode, and resolution is 1280 * 1024.The flying-spot video generator output interface is the YPbPr component signal, and definition is 1920 * 1080i, 50Hz.Test pattern definition scope from 400 tv lines to 900 tv lines.The high speed camera one-time continuous writes down 64 width of cloth images, corresponding 6.4 television images, and algorithm is realized with C++ software.Utilize this cover system respectively a LCD TV (LCD) and a plasm TV (PDP) to be tested.

Consider that the present invention is mainly reflected in human visual system's model emulation algorithm of time domain spatial domain decoupling zero and differentiates algorithm based on " tv line " of modulation degree, therefore relatively divide two processes to carry out, test this 2 point respectively, and get rid of influence each other as far as possible.

What one, at first compare is human visual system's model emulation algorithm of the time domain spatial domain decoupling zero that proposes of the present invention, with original minute frame, an integration and directly the subjective assessment algorithm compare.

Because the evaluating that original field integral algorithm obtains is a discernable obscurity boundary width (PEBW), different with " tv line " of the present invention parameter system, therefore, in order to make the result have comparativity, we adopt subjective assessment in the final step of contrast, the final image that the time-domain filtering algorithm that the final image that the field integral algorithm is obtained and the present invention just proposes obtains carries out subjective assessment, obtain definition of moving images " tv line " index, with directly " tv line " that the motion resolution pattern subjective assessment on the TV obtains compared by human eye, approaching more direct subjective assessment result, illustrate that this algorithm is correct more to human visual system's emulation and modeling, reference as a comparison, we also provide the result of the average back subjective assessment of two field picture in original minute, to confirm the effect of human eye vision system model in final image is handled.

Two, relatively, checking " tv line " based on modulation degree of the present invention differentiated algorithm.

Both sides relatively are " tv lines " that the present invention utilizes the modulation degree algorithm computation to go out " tv line " and directly by human eye the motion resolution pattern subjective assessment on the TV is obtained.Because the evaluating of " integration " that preamble is mentioned, " at a high speed/follow the trail of camera " scheduling algorithm all is a discernable obscurity boundary width (PEBW), different with " tv line " evaluating that the present invention proposes, because those algorithms do not propose a kind of method by the revised image calculation of human visual system's model " tv line ", therefore can't participate in comparison.Below be two-part comparison method and result:

(1) human visual system's model emulation algorithm.

What participate in comparing is the time-domain filtering algorithm that frame, an integration, direct subjective assessment and the present invention in original minute propose.

(1.1) original minute frame.64 width of cloth image subjective assessments one by one with high speed camera is taken pictures continuously are averaged " tv line " result who obtains.

(1.2) integration.10 continuous width of cloth images in 64 width of cloth images that high speed camera is taken pictures continuously mode constant according to relative position or centre of motion alignment is alignd, and to being averaged behind the respective pixel integration, the image after the processing that obtains carries out " tv line " that subjective assessment obtains.

(1.3) directly subjective.Human eye directly carries out " tv line " that subjective assessment obtains to the motion resolution pattern that shows on the TV.

(1.4) algorithm of the present invention.Human visual system's model algorithm of time domain spatial domain decoupling zero.64 width of cloth images that high speed camera is taken pictures continuously, take out the brightness and the chroma data of position to be analyzed pixel according to the constant principle of relative position, then respectively according to human eye time domain Frequency Response illustrated in figures 1 and 2 and the filtering of spatial domain response characteristic, extract the piece image after handling then, carry out " tv line " that subjective assessment obtains.

The comparison result of human visual system's model emulation algorithm after implementing on certain LCD TV test result as shown in Figure 3, the comparison result after implementing on certain plasm TV test result is as shown in Figure 4.

Comparison result: the algorithm decoupling zero that the present invention proposes, that considered human visual system's model of time domain and spatial domain characteristic simultaneously waits the result of the more approaching direct subjective assessment of other algorithms than " integration ", so the most approaching real human visual system of simulation algorithm that proposes of the present invention.

Interpretation of result: the algorithm that the present invention proposes more has following two aspects near the reason of the true vision system of human eye: one is under the situation of computing capability permission, the algorithm that the present invention proposes can be chosen long analytical cycle, for example this paper gets 64 high speed camera sampling periods, corresponding 6 tv field periods.Have only the analytical cycle of 1 TV Field to compare with " integration method ", can effectively avoid " integration method " because the problem of phenomenons " mistakes and omissions " such as " flicker " that the analytical cycle weak point causes, " piece spot ", so analysis result more comprehensively.Another reason is that the algorithm that the present invention proposes has been considered human eye time domain and spatial domain characteristic simultaneously, and the reason of using " time-domain filtering " to replace the existence of " integration " phenomenons such as " persistence of visions " when the time domain specification simulation process is the restriction of time domain frequency response bandwidth, essence is time-domain filtering, " integration " be phenomenon just, therefore algorithm of the present invention is more near human visual system's essence, thereby more approaching with the subjective assessment result.

(2) based on " tv line " computational methods of threshold modulation.

Method for testing definition of moving images such as present existing high speed camera, tracking camera all adopt discernable obscurity boundary width (PEBW) as parameter, and an inventive point of the method for testing that the present invention proposes adopts " tv line " as parameter system exactly, therefore can not be directly and comparison algorithm qualities such as high speed camera, tracking camera.But can with direct subjective assessment result relatively, assess the definition of moving images " tv line " that this algorithm computation obtains and whether have correlation with direct subjective assessment result.If have correlation, size that can the evaluation test error, whether the potential user of this algorithm can adopt this algorithm to be used as the objective computational methods of definition of moving images " tv line " according to the size decision of this error.

Modulation degree M is meant the luminance difference of black and white strip, with black and white strip brightness and ratio, as shown in Figure 5.According to illustrating, the modulation degree of rest image is: ${\mathrm{<figure-callout\; id="0"\; label="M"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">M</figure-callout>}}_0=\frac{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^0-{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^0)}{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^0+{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^0)},$ The modulation degree of moving image is: ${\mathrm{<figure-callout\; id="0"\; label="M"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">M</figure-callout>}}_0=\frac{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^1-{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^1)}{({\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="A2009100913770016H2.png,A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_1^1+{\mathrm{<figure-callout\; id="0"\; label="V"\; filenames="A2009100913770017H2.png"\; state="\{\{state\}\}">V</figure-callout>}}_0^1)}.$ Wherein, V ₀ ⁰Brightness value for the black streaking correspondence in the static resolution chart; V ₁ ⁰Brightness value for the informal voucher line correspondence in the static resolution chart; V ₀ ¹Brightness value for the black streaking correspondence among the exercise test figure; V ₁ ¹Brightness value for the informal voucher line correspondence among the exercise test figure.

The modulation degree discrimination threshold fixes on 5%, if just the modulation degree of certain tv line correspondence of the image of crossing through the time-domain filtering algorithm process of previous step human visual system model is greater than 5%, think that then this tv line can be identified, otherwise can not be identified, can discern and unrecognizable boundary position, be exactly the definition of moving images " tv line " under this movement velocity.Shown in Fig. 6,7 is a LCD TV, when showing the image of 1 pixel/field motion, and the horizontal direction Luminance Distribution at 720 tv lines and 740 tv line places.The modulation degree that calculates 700 lines is that the modulation degree of 7.3%, 720 line is 2.9%, and then the definition of this LCD TV when showing 1 pixel/field moving image is 700 tv lines.

Based on " tv line " computational methods of threshold modulation comparison result after implementing on certain LCD TV test result as shown in Figure 8, the comparison result after implementing on certain plasm TV test result as shown in Figure 9.

Comparison result: the tv line based on " modulation degree " threshold value that the present invention proposes differentiates algorithm and the subjective assessment algorithm has correlation, can be used for calculating definition of moving images " tv line " in certain error range, is a kind of effective calculation.

In sum, according to method for testing definition of moving images of display devices of the present invention, a kind of model of human visual system more accurately is provided, this model has been considered the time domain characteristic and the spatial domain characteristic of human eye simultaneously, and " time-domain filtering " algorithm replaces existing " integration " algorithm with more accurately; In addition, the definition of moving images evaluating and the inconsistent problem of still image definition evaluating of existing method of testing, the present invention adopts " modulation degree " thresholding algorithm to obtain the dynamic image definition, with " tv line " is parameter, consistent with still image definition parameter, can between moving image and still image definition, compare.

More than be in order to make those of ordinary skills understand the present invention; and to detailed description that the present invention carried out; but can expect; in the scope that does not break away from claim of the present invention and contained, can also make other variation and modification, these variations and revising all in protection scope of the present invention.

Claims (9)

1. a method for testing definition of moving images of display devices is characterized in that, comprises the following steps:

Steps A: the exercise test striped of display device or display device is taken and noted to high speed camera continuously;

Step B: carry out the motion tracking preliminary treatment, motion tracking effect according to human eye vision, the image of a plurality of successive frames is constant or align in the mode of centre of motion alignment according to relative position, and take out the brightness and the chroma data of the constant pixel coordinate of relative position;

Step C: the brightness and the chroma data of the pixel coordinate that the relative position of described taking-up is constant carry out time-domain filtering;

Step D: choose the width of cloth test picture behind the time-domain filtering, take out the brightness and the chroma data of the pixel in zone to be analyzed, carry out spatial domain filtering.

2. method for testing definition of moving images of display devices as claimed in claim 1 is characterized in that, further comprises the following steps: before described steps A

Produce chequered with black and white test striped certain movement speed, that fringe spacing and thickness do not wait by flying-spot video generator, and drive tested display device and correctly show this moving image.

3. method for testing definition of moving images of display devices as claimed in claim 2 is characterized in that, in described step C, described time-domain filtering is the processing method that adopts low pass filter filtering; Described spatial domain filtering is the processing method that adopts band-pass filter.

4. method for testing definition of moving images of display devices as claimed in claim 3 is characterized in that, further comprises step e: judge according to the modulation degree threshold values whether certain tv line can be discerned by subjectivity.

5. method for testing definition of moving images of display devices as claimed in claim 4, it is characterized in that, described modulation degree M is meant the ratio of luminance difference with the black and white strip brightness sum of black and white strip, the modulation degree threshold values of certain tv line correspondence of process filtering processed images is greater than 5%, think that then this tv line can be identified, otherwise can not be identified, can discern and unrecognizable boundary position, be exactly the tv line of the definition of moving images under this movement velocity.

6. as claim 4 or 5 described method for testing definition of moving images of display devices, it is characterized in that described step e comprises the following steps:

Step e 1: brightness and the chroma data of described step D being handled a certain tv line in the image of back take out, and form array R ₂(0, j);

Step e 2: find all maximum points and the minimum point of tv line to be analyzed,, m minimum and n maximum should be arranged then if test pattern alternately is made of m black streaking and n informal voucher line with the brightness of position distribution;

Step e 3: according to the brightness data of these maximum value minimum points, calculate modulation degree, should have m, get worst-case value in these modulation degree as the modulation degree of this tv line to n modulation degree by the described formula of preamble;

Step e 4: repeating step E1 calculates the modulation degree of all sampling points that need test to step e 3.Sampling is according to certain analysis spacing;

Step e 5: finding modulation degree near 5% tv line, is exactly result of calculation.

7. method for testing definition of moving images of display devices as claimed in claim 6 is characterized in that, the modulation degree of rest image is: $M_0=\frac{(V_1^0-V_0^0)}{(V_1^0+V_0^0)},$ The modulation degree of moving image is: $M_0=\frac{(V_1^1-V_0^1)}{(V_1^1+V_0^1)},$ Wherein, V ₀ ⁰Brightness value for the black streaking correspondence in the static resolution chart; V ₁ ⁰Brightness value for the informal voucher line correspondence in the static resolution chart; V ₀ ¹Brightness value for the black streaking correspondence among the exercise test figure; V ₁ ¹Brightness value for the informal voucher line correspondence among the exercise test figure.

8. method for testing definition of moving images of display devices as claimed in claim 6, it is characterized in that, the evaluating of definition of moving images measurement result is the evaluating that can directly compare with the still image definition, comprises in " line ", " line to ", " line right/screen size " or " tv line " at least a.

9. method for testing definition of moving images of display devices as claimed in claim 6 is characterized in that, when the test striped was static, the brightness of the pixel in zone to be analyzed on this direction of motion changed by sinusoidal wave distribution:

$G\left(j\right)=\frac{1}{2}(1+\cos (2\mathrm{\&pi;}\&CenterDot;\frac{W_L}{W_0}\&CenterDot;j))\&CenterDot;255$

Wherein, G (j) is this direction of motion of screen upper edge, in the brightness number of j the pixel in zone to be analyzed; W ₀It is this direction physical resolution; W _LIt is the tv line of this black and white strip correspondence; When the test striped moves with v pixel/field, if the brightness of the pixel of position j is G (j) certain the time, then next the time, the brightness of position j+v place pixel also is G (j).

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