CN115706784A - Method for measuring noise of projection image quality of projector and related device - Google Patents
Method for measuring noise of projection image quality of projector and related device Download PDFInfo
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Abstract
The invention discloses a measuring method of noise of projection image quality of a projector, which is characterized in that the higher the probability of repeated occurrence of each noise in a plurality of projection images is, the more stable the noise is, the more visual sense is not influenced, and human eyes feel more comfortable when seeing the noise because the tolerance of the human eyes to unstable noise is lower compared with the stable noise. And calculating the chaos of the projection image through the repetition probability, so that the chaos represents the proportion of unstable noise points in the noise point particles occupying the projection image, the larger the chaos is, the more chaos the human eyes see, the chaos can represent the quality of a projection image projected by a projector, and the measurement of the quality of the projection image is realized. The invention also provides a measuring device of the projector projection image quality noise point, a measuring device of the projector projection image quality noise point and a computer readable storage medium, and the measuring device also have the beneficial effects.
Description
Technical Field
The present invention relates to the field of image quality detection technologies, and in particular, to a method and an apparatus for measuring noise in projected image quality of a projector, a device for measuring noise in projected image quality of a projector, and a computer-readable storage medium.
Background
At present, projectors are mostly implemented based on a DLP (Digital Light Processing) technology, and the DLP technology is mainly based on a DMD (Digital micromirror device) chip for projection. Noise generation is inevitable in the picture projected by the DMD chip, and the noise generation process can also be called high-frequency vibration image error. Because at any instant, the position of each micromirror of the DLP chip is either fully on to exhibit maximum brightness or fully off to exhibit black. DLP micro-lenses do not appear gray by "partially turning on" like the liquid crystal of an LCD. Thus, the DLP chip appears gray by flipping the micro-mirrors back and forth very quickly, which allows the eye to average the "on" and "off states by turning them on for a sufficient time to obtain the desired brightness level, which is known as dithering. It works reasonably well for rendering grey scales but it produces some visible instability in a continuous field, for example most in dark areas, grainy bright spots, a problem known as dithering image errors. The bright spot looks like a digital noise spot, but the bright spot is an image error caused by the DLP technology rather than a signal, and the human senses the jumping of two points, so that the sensory experience effect of the human on the image quality is influenced finally.
At the present stage, no theory is given for the strength measurement standard of the projected noise point, and a proper measurement quantification method and a proper measurement quantification tool for the noise point are not provided at the same time. Therefore, how to quantitatively measure the noise of the projected image quality of the projector is an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a measuring method of the projection image quality noise of a projector, which can measure the projected image quality; another object of the present invention is to provide a measuring apparatus for projecting picture quality noise of a projector, a measuring device for projecting picture quality noise of a projector, and a computer readable storage medium, which can measure the projected picture quality.
In order to solve the above technical problem, the present invention provides a method for measuring noise in projection image quality of a projector, comprising:
acquiring projected images projected by a plurality of target projectors through image acquisition equipment;
extracting noise particles in the projected image;
calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles;
calculating the chaos degree of the projection image according to the repetition probability; the degree of confusion is inversely related to the repetition probability.
Optionally, the calculating, according to the extracted noisy particle, a repetition probability of each noisy particle appearing in each of the projection images includes:
calculating the repeated occurrence times of the noise particles in the projected image according to the noise particles;
when the repeated occurrence frequency is zero, setting the repeated probability corresponding to the noise particles to be zero;
and when the repeated occurrence frequency is more than zero, adding a first preset value to the repeated occurrence frequency and dividing the number of the projected images by the number of the projected images to be used as the repeated probability of the noise particles.
Optionally, the calculating the degree of confusion of the projection image according to the repetition probability includes:
summing the repetition probabilities, and dividing the sum by the number of the noise particles to obtain the noise repetition probability;
and subtracting the noise point repetition probability by using a second preset value to obtain the chaos of the projected image.
Optionally, after extracting the noise particles from the projection image, the method further includes:
fitting the noise particles into a noise graph with a preset shape;
calculating the picture duty ratio of the noise particles according to the area of the noise graph; the picture duty ratio is the proportion of the area of the noise point pattern in the area of the projected image.
Optionally, calculating the picture duty ratio of the noise particles according to the area of the noise pattern includes:
calculating the proportion of the area of the noise point pattern in the projected image in the area corresponding to the projected image, and taking the proportion as the duty ratio of the projected image;
and calculating the average value of all the duty ratios as the picture duty ratio.
Optionally, after the calculating the degree of confusion of the projection image according to the repetition probability, the method further includes:
calculating the intensity value of the noise point according to the duty ratio of the picture and the chaos degree; the intensity of the noise point is positively correlated with the duty ratio of the picture, and the intensity of the noise point is positively correlated with the chaos degree.
Optionally, the slope of the noise level value is positively correlated with the duty ratio of the picture, and the slope of the noise level value is positively correlated with the degree of confusion.
The invention also provides a measuring device for the projection image quality noise of the projector, which comprises:
the acquisition module is used for acquiring projection images projected by a plurality of target projectors through image acquisition equipment;
the extraction module is used for extracting noisy particles in the projection image;
the repeated probability module is used for calculating the repeated probability of the noise particles in the projection image according to the extracted noise particles;
the chaos degree module is used for calculating the chaos degree of the projection image according to the repetition probability; the degree of confusion is inversely related to the repetition probability.
The invention also provides a measuring device for the noise of the projection image quality of the projector, which comprises:
a memory: for storing a computer program;
a processor: the computer program when executed implements a method for measuring projected image quality noise of a projector as described in any of the above.
The present invention also provides a computer readable storage medium, having a computer program stored thereon, where the computer program, when being executed by a processor, implements the steps of the method for measuring the projected image quality noise of a projector according to any of the above.
The invention provides a measuring method of projection image quality noise of a projector, which comprises the steps of obtaining projection images projected by a plurality of target projectors through image acquisition equipment; extracting noise particles in the projected image; calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles; calculating the chaos of the projection image according to the repetition probability; the degree of confusion is inversely related to the probability of repetition.
By counting the probability of each noise point in a plurality of projection images, the higher the probability of the noise point is, the more stable the noise point is, the more the vision is not influenced, and the human eyes feel more comfortable when seeing the noise point, because the tolerance of the human eyes to unstable noise points is lower compared with the stable noise point. And calculating the chaos of the projection image through the repetition probability, so that the chaos represents the proportion of unstable noise points in the noise point particles occupying the projection image, the larger the chaos is, the more chaos the human eyes see, the chaos can represent the quality of a projection image projected by a projector, and the measurement of the quality of the projection image is realized.
The invention also provides a measuring device of the projector projection image quality noise point, a measuring device of the projector projection image quality noise point and a computer readable storage medium, which also have the beneficial effects and are not repeated herein.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a method for measuring noise in projection image quality of a projector according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a method for measuring noise in projection image quality of a projector according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an image acquisition process;
fig. 4 is a block diagram illustrating a structure of a measurement apparatus for measuring noise in projected image quality of a projector according to an embodiment of the present invention;
fig. 5 is a block diagram of a metrology device for projecting image quality noise by a projector according to an embodiment of the present invention.
Detailed Description
The core of the invention is to provide a measuring method for the noise of the projection image quality of the projector. In the prior art, no theory is given at present for the strength measurement standard of the projected noise point, and a proper measurement quantification method and a proper measurement quantification tool for the noise point are not provided at the same time.
The invention provides a measuring method of the projection image quality noise of a projector, which comprises the steps of obtaining projection images projected by a plurality of target projectors through image acquisition equipment; extracting noise particles in the projected image; calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles; calculating the chaos of the projection image according to the repetition probability; the degree of confusion is inversely related to the probability of repetition.
By counting the probability of the recurrence of each noise point in a plurality of projection images, the higher the probability of the recurrence of the noise point is, the more stable the noise point is, the visual sense is not influenced, and human eyes feel more comfortable when seeing the noise point because the tolerance of the human eyes to unstable noise points is lower compared with the stable noise point. And calculating the chaos of the projection image through the repetition probability, so that the chaos represents the proportion of unstable noise points in the noise point particles occupying the projection image, the larger the chaos is, the more chaos the human eyes see, the chaos can represent the quality of a projection image projected by a projector, and the measurement of the quality of the projection image is realized.
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for measuring a noise level of a projected image of a projector according to an embodiment of the present invention.
Referring to fig. 1, in an embodiment of the present invention, a method for measuring a projected image quality noise of a projector includes:
s101: and acquiring projected images projected by the plurality of target projectors through the image acquisition equipment.
In the embodiment of the present invention, it is first required to control the target projector to project the grayscale images, and then in this step, the grayscale images projected by the plurality of target projectors may be continuously captured by the pre-configured image capturing device to form the projection image. Specific contents related to the specific position relationship between the image capturing device and the target projector, the shooting environment, and the like will be described in detail in the following embodiments of the present invention, and will not be described herein again. The number of the projection images specifically acquired in this step may be set by itself according to actual conditions, and is not specifically limited herein. Obviously, the larger the number of projected images, the more accurate the final calculation result.
S102: noisy particles in the projected image are extracted.
In this step, noisy particles need to be extracted from each projection image. In general, in this step, it is necessary to extract noise particles from the projection images by performing processes such as image mean filtering, image addition and subtraction, image enhancement, fourier transform, gaussian convolution, binarization, and morphological processing on each projection image. For the above-mentioned details of extracting noise particles, reference may be made to the prior art, and further description is omitted here.
S103: and calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles.
In this step, the probability that each noise particle in each projection image appears repeatedly in other projection images, that is, the repetition probability, is calculated according to the number of times that each noise particle in each projection image appears repeatedly in other projection images. The detailed calculation process of the repetition probability will be described in detail in the following embodiments of the present invention, and will not be described herein again. In this step, when the repetition probability of a certain noise particle is higher, it means that the noise particle is more stable in the projection screen and flicker is less likely to occur. Thus, the human eye is generally highly tolerant to stationary noise particles, and the higher the repetition probability, the less noticeable the human eye. It should be noted that, when determining whether two noise particles coincide in this step, when the coordinates of the two noise particles are located in the same region, that is, the coordinates of the two noise particles are substantially equal, and when the distance between the coordinates of the two noise particles does not exceed the distance threshold, it can be considered that the two noise particles coincide. The specific value of the size or the distance threshold related to the same area may be set according to the actual situation, and is not limited specifically herein.
S104: and calculating the chaos of the projection image according to the repetition probability.
In an embodiment of the invention, the degree of misordering is inversely related to the repetition probability. The above-mentioned chaos is a proportion of unstable noise in the noise particles occupying the projection image, and the chaos generally needs to be calculated according to the repetition probability of all the noise particles, and the chaos is also generally inversely related to the repetition probability of a certain noise particle, i.e. when the repetition probability of a certain noise particle is very high, the lower its contribution to the chaos is. The specific calculation process of the degree of confusion will be described in detail in the following embodiments of the present invention, and will not be described herein again.
The measuring method for the projection image quality noise of the projector comprises the steps of obtaining projection images projected by a plurality of target projectors through image acquisition equipment; extracting noise particles in the projected image; calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles; calculating the chaos degree of the projection image according to the repetition probability; the degree of confusion is inversely related to the probability of repetition.
By counting the probability of the recurrence of each noise point in a plurality of projection images, the higher the probability of the recurrence of the noise point is, the more stable the noise point is, the visual sense is not influenced, and human eyes feel more comfortable when seeing the noise point because the tolerance of the human eyes to unstable noise points is lower compared with the stable noise point. And calculating the chaos of the projection image through the repetition probability, so that the chaos represents the proportion of unstable noise points in the noise point particles occupying the projection image, the larger the chaos is, the more chaos the human eyes see, the chaos can represent the quality of a projection image projected by a projector, and the measurement of the quality of the projection image is realized.
The detailed description of the method for measuring the noise of the projected image quality of the projector according to the present invention will be described in detail in the following embodiments of the invention.
Referring to fig. 2 and fig. 3, fig. 2 is a flowchart illustrating a method for measuring a noise of a projection image quality of a projector according to an embodiment of the present invention; fig. 3 is a schematic diagram of an image acquisition process.
Referring to fig. 2, in an embodiment of the present invention, a method for measuring a projected image quality noise of a projector includes:
s201: and acquiring projected images projected by the plurality of target projectors through the image acquisition equipment.
Referring to fig. 3, in the embodiment of the present invention, the gray image projected by the projector may be specifically set to be a 5% gray image, and the corresponding projected image in this step may be a 5% gray image, i.e., a 5% gray image, because the noise particles exhibited by the projector are most noticeable when the gray image is a 5% gray image. Of course, the gray-value percentage of the projection image may be between 2% and 20%, inclusive. In embodiments of the present invention, the projection distance of the target projector is typically set at 1500mm to 1856mm, inclusive; the acquisition distance of the image acquisition equipment is usually set to be about 450mm, and the shooting angle is usually set to form an included angle of 0-15 degrees with the normal of the projection surface, including endpoint values; the exposure time of the image pickup apparatus is generally set to 1/125ms, the f-number thereof is generally set to f/6.3, and the sensitivity ISO is generally set to 12800. Specifically, this step generally needs to be performed in a dark environment, i.e., it needs to be ensured that the whole process is performed in the dark when the image acquisition device acquires the projection image, and the projection brightness of the target projector is generally set as a standard.
The rest of this step has already been introduced in S101 in the above embodiment of the present invention, and is not described herein again.
S202: noisy particles in the projected image are extracted.
In this step, it is usually necessary to first divide a region with a fixed position and a width of w × h in the range of 500 pixels to 1500 pixels from each projection image to perform noise image analysis, and it can also be understood that the projection image is referred to as an image with the above size, and then the noise particles are extracted from the projection image by sequentially performing image mean filtering, image addition and subtraction, image enhancement, fourier transform, gaussian convolution, binarization, morphological processing, and the like on the image.
S203: fitting the noise particles into a noise pattern of a predetermined shape.
In step (iii), a circle fit is typically specifically performed for each noisy particle to fit the noisy particles into a circle. Of course, the noise particles can also be fitted to other patterns in this step, and are not specifically limited herein as the case may be. When fitting the noise particles to a circle, the radius of the circle can be used to represent the value of the particle size per noise r i In particular, in embodiments of the present invention, the average of all of the radii of the noisy pattern in each projection image may be used as the size value of noisy particles in that projection image. That is, in the embodiment of the present invention, the size of each noise point in a single projection image can be calculated as r 1 ，r 2 ，r 3 ，…r m And finally, the size value of the noise particles in the projection image is as follows:
thereafter, n Zhang Tou may be countedThe noise particle number in the photographic image is s 1 ，s 2 ，s 3 ，…，s n 。
S204: and calculating the picture duty ratio of the noise particles according to the area of the noise graph.
In an embodiment of the present invention, the screen duty ratio is a ratio of the noise pattern area to the projected image area.
In this step, the ratio of the noise particles occupying the area of the projected image picture, i.e. the picture duty ratio, is calculated according to the area of the noise pattern fitted in S03. The higher the duty cycle of the picture, the more obvious noise is in the picture and the more easily recognized by human eyes.
Specifically, the present step generally specifically includes the following S2041 and S2042: s2041, calculating the proportion of the area of the noise point graph in the projection image to the area of the corresponding projection image as the duty ratio of the projection image.
In this step, the area a = w × h of the projection image may be first calculated, and then the noise particle size value r in each projection image and the noise particle number s corresponding to each projection image may be based on the above values n The area A occupied by the noise particles in each projection image can be calculated Noise point ：
A Noise point ＝s n πr 2 ；
The duty cycle of the area of the noisy particles in each projection image can then be calculated:
Ac＝A/A noise point ；
At this time, the duty ratios of the n projection images are Ac 1 ，Ac 2 ，…，Ac n 。
S2042, calculate the average of all duty cycles as the picture duty cycle.
In this step, the picture duty ratio Ac is specifically calculated Average ：
The picture duty ratio can represent the proportion of noise particles in the whole picture, and the higher the picture duty ratio is, the more obvious the noise is in the picture, and the more easily recognized by human eyes.
S205: the number of noise particles that recur in the projection image is calculated from the noise particles.
In this step, the number of times c that each noise point in each projection image can be repeated is counted, that is, the number of times that the j noise point particle in the i projection image is repeated at the same position as the other n-1 projection images is counted, so as to calculate the repetition probability of the noise point particle.
S206: and when the repeated occurrence frequency is zero, setting the repeated probability of the corresponding noise particles to be zero.
S207: and when the repeated occurrence frequency is more than zero, adding the repeated occurrence frequency to a first preset value and dividing the result by the number of the projection images to be used as the repeated probability of the noise particles.
The first preset value is usually 1, and certainly, the first preset value may have other values in other calculation processes, which is not specifically limited herein. In the embodiment of the present invention, the repetition probability P of the jth noise particle in the ith projection image is specifically calculated by the following formula i，j ：
Where n is the total number of projected images, when c =0, it means that the noise particle appears only once in n projected images, and the probability of repetition of the noise particle is 0; when repeated once, it means that noisy particles occur twice in total in n projection images at the same position, and thus the repetition probability is 2/n. In the embodiment of the invention, the repetition probability P of each noise particle in each projection image needs to be calculated in turn 1,1 ，P 1,2 ，…，P n，Sn 。
S208: and summing the repetition probabilities, and dividing the sum by the number of the noise particles to obtain the noise repetition probability.
In this step, first the number S of all noise particles needs to be calculated:
then the noise repetition probability P needs to be calculated:
s29: and subtracting the noise repetition probability by using a second preset value to obtain the chaos of the projected image.
The second preset value is usually 1, and of course, other values may be available in the second preset value in different calculation processes, depending on the specific situation. In this step, the degree of confusion P' is calculated:
P’＝1-P；
the degree of clutter is the proportion of unstable noise in the noise particles that occupies the projected image. It should be noted that, the calculation process of the degree of confusion and the calculation process of the picture duty ratio may be executed in parallel, that is, there is no absolute precedence relationship between the above-mentioned S203 to S205 and S206 to S210, and one of the two parts is executed first, or both of the two parts are executed in parallel, as the case may be. The deficiency is specifically limited.
S210: and calculating the intensity value of the noise point according to the duty ratio and the chaos degree of the picture.
In the embodiment of the present invention, the noise level is positively correlated with the duty ratio of the picture, and the noise level is positively correlated with the degree of confusion.
In this step, the noise level value may be calculated by combining the duty ratio of the picture calculated in S205 and the degree of confusion calculated in S210, where the noise level value directly reflects the noise level of the picture projected by the target projector. Specifically, in the embodiment of the present invention, the intensity of the noise is positively correlated with the duty ratio of the picture, and the intensity of the noise is positively correlated with the degree of confusion. Because the intensity of noise of one projection device is closely related to the particle size and the particle disorder degree of the noise, the noise of different types of projection devices is large in size, people can feel that the noise is strong in the first sense, and then the noise is weak in sense as the jitter of the noise in the same region is smaller according to the disorder degree of the particles of the noise. Therefore, in the step, the sense of seeing things is simulated for carrying out data measurement on the intensity of the noise point, and the problem that the intensity results of the noise points seen by different people are inconsistent is solved.
Specifically, in the embodiment of the present invention, in a normal case, a slope of the noise level value is positively correlated with the picture duty ratio, and a slope of the noise level value is positively correlated with the degree of confusion. Namely, the intensity of the noise point can increase faster and faster along with the increase of the chaos degree; accordingly, as the duty ratio of the picture is increased, the intensity of the noise point is increased more and more quickly.
In general, the step may specifically be: and taking a preset first base number as a base, subtracting the logarithm of the chaos degree from a third preset value, multiplying the logarithm of the chaos degree by a preset second base number as a base, and subtracting the logarithm of the picture duty ratio from a fourth preset value as the noise intensity value. The preset first base number and the preset second base number may be e, and the second third preset value and the fourth preset value are 1. Of course, specific values of the preset first base number, the preset second base number, the preset third value and the preset fourth value may be set according to actual situations, and are not limited specifically herein. In this step, the noise level NOI may be specifically calculated by the following formula:
NOI＝ln(1-P′)×ln(1-Ac average )
Due to the above-mentioned chaos P' and the picture duty Ac Average The value range of (1) is between 0 and 1, including end point values, the larger the value calculated by the formula is, the larger the noise intensity of the target projector is, the larger the chaos degree of noise particles is, the stronger the noise is in human vision, so that the larger the NOI value is, and the trend is consistent with human sense; the larger the duty ratio of the projection equipment with the same chaos degree is, the larger or more noisy particles are represented, the occupied picture space is large, and people feel that the intensity of noisy points is also stronger. With increasing degree of disorder and picture duty ratioThe tolerance of human eyes to the picture is worse and worse, and the picture is more practical. The intensity of noise points is measured by using the duty ratio and the chaos degree of the picture, so that the problems of deviation caused by position change of projection equipment and position and focal length change of acquisition equipment are reduced, the characteristic of the projection picture is realized, and the stability and the accuracy of a measurement result are facilitated.
The measuring method for the projection image quality noise of the projector provided by the embodiment of the invention simulates the sense of things seen by people to carry out data measurement on the intensity of the noise, and solves the problem that the intensity results of the noise seen by different people are inconsistent. The intensity of noise points is measured by specifically using the duty ratio and the chaos degree of the picture, so that the problems of the position change of projection equipment and the deviation caused by the position and the focal length change of the acquisition equipment are reduced, the characteristic of the projection picture is realized, and the stability and the accuracy of a measurement result are facilitated.
The following describes an apparatus for measuring projected image quality noise of a projector according to an embodiment of the present invention, and the apparatus for measuring projected image quality noise of a projector described below and the method for measuring projected image quality noise of a projector described above may be referred to in correspondence.
Referring to fig. 4, fig. 4 is a block diagram illustrating a structure of a measurement apparatus for measuring a projected image quality noise of a projector according to an embodiment of the present invention. Referring to fig. 4, the metric apparatus for projecting the picture quality noise by the projector may include:
the acquisition module 100 is configured to acquire projection images projected by a plurality of target projectors through an image acquisition device.
And an extracting module 200, configured to extract noise particles in the projection image.
A repetition probability module 300, configured to calculate a repetition probability of a noisy particle appearing repeatedly in the projection image according to the extracted noisy particle.
A degree of confusion module 400 for calculating the degree of confusion of the projection image according to the repetition probability; the degree of confusion is inversely related to the repetition probability.
Preferably, in an embodiment of the present invention, the repetition probability module 300 includes:
and the frequency counting unit is used for calculating the frequency of repeated occurrence of the noise particles in the projection image according to the noise particles.
And the zero setting unit is used for setting the repetition probability corresponding to the noise particles to be zero when the repeated occurrence frequency is zero.
And the calculating unit is used for adding the repeated times to a first preset value and dividing the added times by the number of the projection images to be used as the repeated probability of the noise particles when the repeated times are more than zero.
Preferably, in the embodiment of the present invention, the chaos module 400 includes:
and the summing unit is used for summing the repetition probabilities and dividing the sum by the number of the noise particles to obtain the noise repetition probability.
And the chaos unit is used for subtracting the noise point repetition probability from a second preset value to obtain the chaos of the projected image.
Preferably, in the embodiment of the present invention, the method further includes:
and the pattern fitting module is used for fitting the noise point particles into a noise point pattern with a preset shape.
The picture duty ratio module is used for calculating the picture duty ratio of the noise particles according to the area of the noise figure; the picture duty ratio is the proportion of the area of the noise point pattern in the area of the projected image.
Preferably, in an embodiment of the present invention, the picture duty module includes:
and the duty ratio unit is used for calculating the proportion of the area of the noise point pattern in the projected image in the area corresponding to the projected image as the duty ratio of the projected image.
And the picture duty ratio unit is used for calculating the average value of all the duty ratios as the picture duty ratio.
Preferably, in the embodiment of the present invention, the method further includes:
the noise intensity value module is used for calculating a noise intensity value according to the picture duty ratio and the chaos degree; the intensity of the noise point is positively correlated with the duty ratio of the picture, and the intensity of the noise point is positively correlated with the chaos degree.
Preferably, in an embodiment of the present invention, a slope of the noise level value is positively correlated with the picture duty ratio, and a slope of the noise level value is positively correlated with the degree of confusion.
Preferably, in the embodiment of the present invention, the projection distance of the target projector ranges from 1500mm to 1856mm, inclusive.
The measurement apparatus for measuring projected image quality noise of a projector according to this embodiment is used to implement the measurement method for measuring projected image quality noise of a projector, and therefore specific embodiments of the measurement apparatus for measuring projected image quality noise of a projector can be found in the foregoing embodiments of the measurement method for measuring projected image quality noise of a projector, for example, the acquisition module 100, the extraction module 200, the repetition probability module 300, and the confusion degree module 400 are respectively used to implement steps S101 to S104 in the measurement method for measuring projected image quality noise of a projector, and therefore, the specific embodiments thereof may refer to descriptions of corresponding embodiments of each part, and are not described herein again.
The following describes a measuring apparatus for projecting picture quality noise by a projector according to an embodiment of the present invention, and the measuring apparatus for projecting picture quality noise by a projector described below, the measuring method for projecting picture quality noise by a projector described above, and the measuring device for projecting picture quality noise by a projector described above may be referred to in correspondence with each other.
Referring to fig. 5, fig. 5 is a block diagram illustrating a configuration of a metrology device for projecting image quality noise by a projector according to an embodiment of the present invention.
Referring to fig. 5, the metrology device that projects the picture quality noise from the projector may include a processor 11 and a memory 12.
The memory 12 is used for storing a computer program; the processor 11 is configured to implement the specific content of the method for measuring the projected image quality noise of the projector according to the embodiment of the present invention when the computer program is executed.
The processor 11 of the measuring apparatus for projecting image quality noise of the projector according to the embodiment of the present invention is used to install the measuring apparatus for projecting image quality noise of the projector according to the embodiment of the present invention, and the processor 11 and the memory 12 are combined to implement the measuring method for projecting image quality noise of the projector according to any one of the embodiments of the present invention. Therefore, the specific implementation of the measurement apparatus for projecting the noise quality of the projector can be found in the foregoing embodiments of the measurement method for projecting the noise quality of the projector, and the specific implementation thereof can refer to the description of the corresponding embodiments of each part, and is not described herein again.
The present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for measuring noise in projection image quality of a projector is implemented as described in any of the embodiments of the present invention. The rest can be referred to the prior art and will not be described in an expanded manner.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The detailed description of the method for measuring the projected image quality noise of the projector, the device for measuring the projected image quality noise of the projector and the computer readable storage medium provided by the invention are provided above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, it is possible to make various improvements and modifications to the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. A method for measuring the noise of the projection image quality of a projector is characterized by comprising the following steps:
acquiring projected images projected by a plurality of target projectors through image acquisition equipment;
extracting noise particles in the projected image;
calculating the repeated probability of the repeated occurrence of the noise particles in the projection image according to the extracted noise particles;
calculating the chaos degree of the projection image according to the repetition probability; the degree of confusion is inversely related to the repetition probability.
2. The method of claim 1, further comprising:
calculating the intensity value of the noise point according to the chaos degree and the picture duty ratio;
the picture duty ratio is the proportion of the area of the noise particle fitting graph in the area of the projected image, the noise strength value is in positive correlation with the picture duty ratio, and the noise strength value is in positive correlation with the chaos degree.
3. The method of claim 1, wherein said calculating a probability of repetition of each noisy particle occurrence in each of said projection images from said extracted noisy particles comprises:
calculating the repeated occurrence times of the noise particles in the projected image according to the noise particles;
when the repeated occurrence frequency is zero, setting the repeated probability corresponding to the noise particles to be zero;
and when the repeated occurrence frequency is more than zero, adding the repeated occurrence frequency to a first preset value and dividing the number by the number of the projection images to be used as the repeated probability of the noise particles.
4. The method of claim 3, wherein said computing a degree of clutter of the projection images from the probability of repetition comprises:
summing the repetition probabilities, and dividing the sum by the number of the noise particles to obtain the noise repetition probability;
and subtracting the noise point repetition probability by using a second preset value to obtain the chaos of the projected image.
5. The method of claim 1, further comprising, after said extracting noisy particles from said projection images:
fitting the noise particles into a noise graph with a preset shape;
calculating the picture duty ratio of the noise particles according to the area of the noise figure; the picture duty ratio is the proportion of the area of the noise point pattern in the area of the projected image.
6. The method of claim 5, wherein calculating the picture duty cycle of the noise particles based on the area of the noise pattern comprises:
calculating the proportion of the area of the noise point pattern in the projected image in the area corresponding to the projected image, and taking the proportion as the duty ratio of the projected image;
and calculating the average value of all the duty ratios as the picture duty ratio.
7. The method of claim 5, further comprising, after said calculating a degree of misordering of the projection images based on the probability of repetition:
calculating the intensity value of the noise point according to the duty ratio of the picture and the chaos degree; the intensity of the noise point is positively correlated with the duty ratio of the picture, and the intensity of the noise point is positively correlated with the chaos degree.
8. A device for measuring a noise level of a projected image of a projector, comprising:
the acquisition module is used for acquiring projection images projected by a plurality of target projectors through image acquisition equipment;
the extraction module is used for extracting noise particles in the projection image;
the repeated probability module is used for calculating the repeated probability of the noise particles in the projection image according to the extracted noise particles;
the chaos degree module is used for calculating the chaos degree of the projection image according to the repetition probability; the degree of confusion is inversely related to the repetition probability.
9. A metrology apparatus for projecting image quality artifacts with a projector, the apparatus comprising:
a memory: for storing a computer program;
a processor: steps for implementing a method for measuring projected picture quality noise of a projector according to any one of claims 1 to 7 when executing said computer program.
10. A computer-readable storage medium, having a computer program stored thereon, which, when being executed by a processor, performs the steps of the method for measuring projected picture quality noise of a projector according to any one of claims 1 to 7.
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