CN108711153B - Digital video image distortion detection method - Google Patents
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- CN108711153B CN108711153B CN201810534435.2A CN201810534435A CN108711153B CN 108711153 B CN108711153 B CN 108711153B CN 201810534435 A CN201810534435 A CN 201810534435A CN 108711153 B CN108711153 B CN 108711153B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/10—Image acquisition modality
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Abstract
The invention provides a digital video image distortion detection method, which comprises the following steps: judging whether the video image detection mode is a video frame detection mode or not according to the received detection instruction; when the video image detection mode is judged to be the video frame detection mode, generating a video frame detection image; calculating a frame difference value between any frame loopback graphic in the video frame loopback image and a sample graphic of a corresponding frame in the video frame detection image according to the received video frame loopback image and the video frame detection image; and generating a video frame detection result according to the frame difference value. By the technical scheme, the reliability of the distortion detection of the video content is improved, and the accuracy and the quality detection efficiency of the quality detection of the image processing equipment are improved.
Description
Technical Field
The invention relates to the technical field of video detection, in particular to a digital video image distortion detection method.
Background
After the digital video image is processed by the image processing device, the digital video image is displayed by the image display device, and due to the problems or faults of the image processing device, the processed digital video image has certain distortion, which affects the watching effect of a user. In general, the factors causing image distortion are:
(1) the positions of image pixel points are deviated;
(2) the color content of the image has changed;
(3) the image has frame insertion, frame loss or frame disorder.
In the prior art, a sample image and a sample loop-back image processed by an image processing device are usually displayed on a display device, and a human eye of a detection person recognizes a difference between the sample loop-back image and the sample image.
Disclosure of Invention
The present invention is directed to solving at least one of the problems in the prior art or the related art.
Aiming at the problems, the invention provides a digital video image distortion detection method, which improves the accuracy of digital video image content distortion detection and is beneficial to improving the reliability of image processing equipment fault detection.
In order to achieve the above object, the present invention provides a digital video image distortion detection method, including: step 10, judging whether a video image detection mode is a video frame detection mode or not according to a received detection instruction; step 20, when the video image detection mode is judged to be the video frame detection mode, generating a video frame detection image; step 30, calculating a frame difference value between any frame loopback image in the video frame loopback image and a sample image of a corresponding frame in the video frame detection image according to the received video frame loopback image and the video frame detection image; and step 40, generating a video frame detection result in unit detection time according to the frame difference value.
In any one of the above technical solutions, preferably, the step 20 specifically includes: step 21, obtaining the resolution and image frame information of a video frame detection image; step 22, calculating the color value of a pixel point in a video frame detection image according to the resolution and the image frame information; and step 23, generating a video frame detection image according to the color value and the preset scanning frequency, wherein the image frame information comprises a frame number.
In any one of the above technical solutions, preferably, the step 30 further specifically includes: step 31, selecting at least one pixel point in a sample image and recording the pixel point as a video frame sample point; step 32, obtaining loop-back image pixel points of each frame in the video frame loop-back image corresponding to the video frame sample points, and recording the loop-back image pixel points as video frame detection points; step 33, calculating a pixel difference value of a video frame detection point in two adjacent frames; and step 34, generating a video frame detection result according to the pixel difference value.
In any one of the above technical solutions, preferably, the step 10 further includes: step 11, when the video image detection mode is judged not to be the video frame detection mode, judging whether the video image detection mode is the offset detection mode; step 12, when the video image detection mode is judged to be the offset detection mode, generating an offset detection image; step 13, calculating the position offset of any pixel point in the offset loopback image according to the received offset loopback image and the offset detection image; and step 14, generating an offset detection result according to the position offset.
In any one of the above technical solutions, preferably, step 11 further includes: step 15, when the video image detection mode is judged not to be the offset detection mode, generating a distortion detection image; step 16, determining a pixel distortion point in the distortion loopback image according to the received distortion loopback image and the distortion detection image; step 17, calculating a pixel distortion value corresponding to the pixel distortion point; and step 18, generating a distortion detection result according to the pixel distortion point and the pixel distortion value.
In any one of the above technical solutions, preferably, the method further includes: step 50, determining a first display mode according to the detection instruction; and step 60, sending a detection result according to the first display mode, wherein the detection result comprises a video frame detection result, an offset detection result and a distortion detection result.
In any one of the above technical solutions, preferably, the method further includes: step 70, determining a second display mode according to the received result display instruction; and step 80, sending the detection result according to the second display mode.
Has the advantages that:
the technical scheme of the invention is used for detecting the distortion of the digital video image, and is beneficial to improving the accuracy of the generated sample image, improving the obvious degree of the distortion of the sample loop-back image when the image processing device is abnormal, improving the reliability of calculating the difference between the sample image and the sample loop-back image and improving the reliability of the detection of the coding and decoding quality by judging the video image detection mode.
According to the invention, different display modes are set, and the display mode of the image detection result is adjusted, so that the image distortion detection result can be displayed visually, the complexity of judging the abnormality of the image processing device according to the image detection result is reduced, and the quality detection efficiency of the image processing device can be improved.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow diagram of a digital video image distortion detection method according to one embodiment of the present invention;
FIG. 2 is a simulated view of a distortion detection image according to one embodiment of the invention;
FIG. 3 is a block diagram illustrating the detection results according to one embodiment of the present invention;
FIG. 4 is a block diagram illustrating the detection results according to another embodiment of the present invention;
fig. 5 is a schematic block diagram of a digital video image distortion detection apparatus according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
The first embodiment is as follows:
a first embodiment of the present application will be described with reference to fig. 1 to 4.
Fig. 1 shows a schematic flow diagram of a digital video image distortion detection method according to an embodiment of the invention.
FIG. 2 shows a simulation of a distortion detection image according to one embodiment of the invention.
Fig. 3 shows a schematic block diagram of the detection result according to an embodiment of the invention.
Fig. 4 shows a schematic block diagram of the detection result according to another embodiment of the present invention.
As shown in fig. 1, a digital video image distortion detection method according to an embodiment of the present invention includes:
the detection instruction is divided into a video frame detection instruction, an offset detection instruction and a distortion detection instruction, and the corresponding video image detection modes are a video frame detection mode, an offset detection mode and a distortion detection mode respectively.
Step 20, when the video image detection mode is judged to be the video frame detection mode, generating a video frame detection image;
the method specifically comprises the following steps:
step 21, obtaining the resolution and image frame information of a video frame detection image;
specifically, in the digital video image distortion detection system, the scanning frequency of a video frame detection image is set to be 60Hz, the image resolution is 1920 × 1080, the frame number of the image is 256, the abscissa of a pixel is x, the ordinate of the pixel is y, and the frame number corresponding to the current time is z. By obtaining the resolution of the video frame detection image and the image frame information, it can be determined that the value range of x is [0, 1919], the value range of y is [0, 1079], and the value range of z is [0, 255], wherein, after the coordinates of the pixel point are changed from (1919, 1079) to (0, 0), the value of the frame number z is added with 1, and the frame number is considered to be continuous from 255 to 0.
Step 22, calculating the color value of a pixel point in a video frame detection image according to the resolution and the image frame information;
and step 23, generating a video frame detection image according to the color value and the preset scanning frequency, wherein the image frame information comprises a frame number.
Specifically, in the process of generating a video frame detection image, when generating a graph of each frame according to the CEA-861 standard, the RGB color values of the corresponding pixel points are calculated according to the abscissa x, the ordinate y, the current frame number z, and a preset remainder function, where the preset remainder function is:
wherein, x belongs to [0, 1919] in abscissa, z belongs to [0, 1079] in ordinate, and z belongs to [0, 255] in frame number.
the method specifically comprises the following steps:
step 31, selecting at least one pixel point in a sample image and recording the pixel point as a video frame sample point;
step 32, obtaining loop-back image pixel points of each frame in the video frame loop-back image corresponding to the video frame sample points, and recording the loop-back image pixel points as video frame detection points;
step 33, calculating a pixel difference value of a video frame detection point in two adjacent frames;
and step 34, generating a video frame detection result according to the pixel difference value.
Specifically, the video frame detection image generated according to the method is an image which changes according to frame number changes, and the color value of any pixel point is determined by the current frame number, so that whether frame insertion, frame loss or frame disorder occurs after the video frame detection image is processed can be calculated according to the color value of any pixel point, and whether the problem of frame processing continuity exists in the image processing equipment is further judged.
Further, when the coordinate of the selected pixel point is determined to be (960, 540), the pixel point is marked as a first image sampling point, the frame number of the current video frame detection image is set to be 10, and the RGB value of the corresponding first sampling point is set to be (10, 10, 10).
When the current frame number of the video frame loopback image is detected to be 8, selecting a pixel point with coordinates (960, 540) in the video frame loopback image, recording the pixel point as a second sampling point, calculating the RGB value of the second sampling point, and when the RGB value of the second sampling point is determined to be (8, 8, 8), calculating the RGB difference value of the first sampling point and the second sampling point, wherein the corresponding difference value is (2, 2, 2), so that the delay of the RGB components of the video frame loopback image at the current moment can be judged to be 2 frames. If the delay threshold set at this time is 3 frames, it can be determined that the current detected image is normal.
Furthermore, 2 continuous frames before the current frame number 8 of the video frame loopback image are selected, pixel points with coordinates (960, 540) are selected, the pixel points are sequentially recorded as a third sampling point and a fourth sampling point, and the RGB values of the third sampling point and the fourth sampling point and the RGB difference between two adjacent pixel points are calculated.
When the RGB value of the third sampling point is determined to be (7, 7, 7) and the RGB value of the fourth sampling point is determined to be (6, 6, 6), the RGB difference values between the second sampling point and the third sampling point and between the third sampling point and the fourth sampling point are (1, 1, 1), and it can be judged that no frame loss or frame insertion occurs between three frames corresponding to the video frame loopback image.
When the RGB values of the third sample point and the fourth sample point are determined to be (6, 6, 6) and (5, 5, 5), the difference between RGB values of the second and third sample points is (2, 2, 2), and the difference between RGB values of the third and fourth sample points is (1, 1, 1), it can be determined that frame loss occurs between the 8 th frame (current frame) of the video frame loopback image and the previous frame, and the frame loss frequency is increased by 1 time.
When the RGB values of the third sample point and the fourth sample point are determined to be (7, 7, 7, 7), the difference value between RGB of the second sample point and the third sample point is (1, 1, 1), and the difference value between RGB of the third sample point and the fourth sample point is (0, 0, 0), it can be determined that the frame interpolation occurs before the 8 th frame (current frame) of the loop image of the video frame, and the frame interpolation frequency is increased by 1 time.
When the RGB value of the third sampling point is determined to be (9, 9, 9) and the RGB value of the fourth sampling point is determined to be (6, 6, 6), the RGB difference value between the second sampling point and the third sampling point is (255, 255, 255), the frame disorder between the 8 th frame (current frame) and the previous frame of the video frame loopback image can be judged, and the frame disorder times are increased by 1 time.
And step 40, generating a video frame detection result in unit detection time according to the frame difference value.
The frame detection result may include the frame dropping times, the frame dropping frame number, the frame inserting times, the frame inserting frame number, the frame disordering times, the frame disordering frame number and the frame disordering frame number, and the unit detection time may be set to 1 second.
In any of the above embodiments, step 10 preferably further includes:
step 11, when the video image detection mode is judged not to be the video frame detection mode, judging whether the video image detection mode is the offset detection mode;
step 12, when the video image detection mode is judged to be the offset detection mode, generating an offset detection image;
specifically, when the digital video image is subjected to offset detection, whether the digital video image has been offset or not is determined by using a specific image coordinate comparison method, that is, an offset detection image having a specific shape and a specific pixel value is generated.
The scanning frequency of a video frame detection image is set to be 60Hz, the image resolution is 1920 multiplied by 1080, the value range of the abscissa x of the pixel point is [0, 1919], and the value range of the ordinate y of the pixel point is [0, 1079 ]. When the video image detection mode is judged to be the offset detection mode, calculating the RGB color value of the corresponding pixel point according to a preset offset point pixel formula to generate an offset detection image, wherein the preset offset point pixel formula is as follows:
that is, the generated shift detection image is an image in which four corners are divided into white blocks each having a width of 3 pixels, one white block having a width of 6 is disposed at the center, and the remaining positions are black.
Step 13, calculating the position offset of any pixel point in the offset loopback image according to the received offset loopback image and the offset detection image;
specifically, a 3x3 white pixel dot matrix is generated at four vertices in the offset detection image, and is respectively marked as a square a, a square B, a square C, and a square D, and a 6x6 white pixel dot matrix is formed with the pixels (957, 537) as a starting point, and is marked as a reference square E.
And obtaining the coordinate of the first pixel point in a white square with the side length of 6 pixels in the offset loopback image, calculating the position offset between the coordinate of the pixel point and the coordinate (957, 537) of the pixel point in the reference square E, and correcting the offset loopback image according to the obtained position offset to obtain an offset correction image.
And respectively calculating the position offset between the coordinate of the first pixel point in the white pixel point lattice of 4 side lengths of 3 pixels in the offset correction image and the corresponding pixel point coordinates (0, 0), (0, 1077), (1917, 0) and (1917, 1077), and when at least one of the four calculated position offsets is judged to be zero, determining that the position offset calculated according to the reference square E is accurate, otherwise, recalculating the position offset of the reference square E, and avoiding obtaining wrong position offset due to error codes.
When the amount of any positional shift in the calculated shift-corrected image is (0, 0), it is expected that no shift occurs in the process of processing the shift-detected image by the device under test. Otherwise, an offset occurs.
And step 14, generating an offset detection result according to the position offset.
The offset detection result may include the number of offset points, coordinates of the offset points, an offset amount of the offset points, an offset direction, and an offset correction value.
In any of the above embodiments, preferably, step 11 further comprises:
step 15, when the video image detection mode is judged not to be the offset detection mode, generating a distortion detection image;
specifically, as shown in fig. 2, the scanning frequency of the detected image of the video frame is set to be 60Hz, the image resolution is 1920 × 1080, the range of x, the abscissa of the pixel, is [0, 1919], and the range of y, the ordinate of the pixel, is [0, 1079 ]. When the video image detection mode is judged to be the distortion detection mode, calculating the RGB color value of the corresponding pixel point according to a preset pixel block formula, and generating a distortion detection image, wherein the preset pixel block formula is as follows:
wherein, & is bitwise AND operation, that is, a distortion detection image with non-repeated pixel points in any 256 × 256 area is generated.
Step 16, determining a pixel distortion point in the distortion loopback image according to the received distortion loopback image and the distortion detection image;
step 17, calculating a pixel distortion value corresponding to the pixel distortion point;
and step 18, generating a distortion detection result according to the pixel distortion point and the pixel distortion value.
Specifically, pixel values of each pixel point in the distortion loopback image and the distortion detection image are compared point by point, and the color depth is set to be 8 bits, that is, three components of the RGB value of each pixel point are 8 bits. When comparing, starting from the first point (x is 0, y is 0, and the coordinate is (0, 0)) at the upper left corner of the distortion detection image and the distortion loop-back image, and going to the last point (x is 1919, y is 1079, and the coordinate is (1919, 1079)) at the lower right corner of the distortion detection image and the distortion loop-back image, the three components of RGB of each pixel point are compared in order of bits, that is, the highest bit of each component is compared first, and then the next highest bit of each component is compared until the lowest bit of each component. And counting and recording the comparison result of each time, and judging whether the distorted loopback image is distorted or not.
The distortion detection result may include the number of distortion points, coordinates of the distortion points, and pixel distortion values of the distortion points.
In any one of the above embodiments, preferably, the method further includes:
step 50, determining a first display mode according to the detection instruction;
and step 60, sending a detection result according to the first display mode, wherein the detection result comprises a video frame detection result, an offset detection result and a distortion detection result.
Specifically, as shown in fig. 3, in the first display mode, part of content 4 is set and displayed, which is a sample image, a sample loop-back image, an image contrast, and detection data, so as to improve the result of rapid acquisition of video image distortion detection by a detection person.
The method comprises the steps of obtaining a sample image, a sample loopback image, an image contrast and detection data, wherein the sample image is one of a video frame detection image, an offset detection image and a distortion detection image, the sample loopback image is one of a corresponding video frame loopback image, an offset loopback image and a distortion loopback image, the image contrast is the contrast between the sample image and the sample loopback image, and the detection data is one of a corresponding video frame detection result, an offset detection result and a distortion detection result.
In any one of the above embodiments, preferably, the method further includes:
step 70, determining a second display mode according to the received result display instruction; and step 80, sending the detection result according to the second display mode.
Specifically, taking offset detection as an example, as shown in fig. 4, when offset detection is performed, before a result display instruction is not received, a detection result is transmitted according to a first display mode, and the transmitted content includes four parts, namely, an offset detection image 4(a), an offset loopback image 4(B), an image contrast 4(C), and an offset detection result 4(D), that is, four parts of content are simultaneously displayed on a display device.
After receiving the result display instruction, according to the result display instruction, only one of the shift detection image 4(a), the shift loop-back image 4(B), the image contrast 4(C) and the shift detection result 4(D) may be sent to the display device for display in a separate display manner, or one of the shift detection image 4(a), the shift loop-back image 4(B), the image contrast 4(C) and the shift detection result 4(D) may be sent to the display device for display in a loop play manner, so that the detection personnel can confirm the display and the reliability of digital video image distortion detection is improved.
Example two:
fig. 5 shows a schematic block diagram of a digital video image distortion detection apparatus according to an embodiment of the present invention.
As shown in fig. 5, the digital video image distortion detection apparatus 500 according to an embodiment of the present invention includes: a detection mode selection module 502, a sample image generation module 504, an image comparison detection module 506, a result output module 508, a result display control module 510, and an image receiving module 512.
A detection mode selection module 502, a first output end of the detection mode selection module 502 is electrically connected to an input end of the sample image generation module 504, a second output end of the detection mode selection module 502 is electrically connected to a third input end of the image comparison detection module 506, and the detection mode selection module 502 is configured to control the sample image generation module 504 to generate a sample image corresponding to a preset detection mode; the detection mode selection module 502 is further configured to send a detection mode control signal to the image comparison detection module 506 according to a preset detection mode.
Specifically, the detection mode selection module 502 receives an external detection instruction through the I/O interface, determines a detection mode type corresponding to the received detection instruction, and sends a determination result to the sample image generation module 504 and the image comparison detection module 506.
Wherein the detection modes include a video frame detection mode, an offset detection mode, and a distortion detection mode.
The output end of the sample image generation module 504 is electrically connected to the image sending interface 514, and the sample image generation module 504 is used for generating and sending a sample image.
Specifically, the image generation module 504 generates a sample image corresponding to the detection mode according to the received detection mode determination result, on one hand, the image generation module 504 transmits the generated sample image to the digital video image processing apparatus through the image transmission interface 514 as a sample image to be processed, and on the other hand, the image generation module 504 transmits the generated sample image to the image comparison detection module 506 as a reference for image comparison.
Wherein the sample image includes a video frame detection image, an offset detection image, and a distortion detection image.
The input end of the image receiving module 512 is electrically connected to the image receiving interface 516, and the image receiving module 512 is used for collecting a sample loop image through the interface;
and a first input end of the image comparison detection module 506 is electrically connected to the output end of the image receiving module 512, a second input end of the image comparison detection module 506 is electrically connected to the output end of the sample image generation module 504, and the image comparison inspection module is used for detecting the difference between the sample image and the sample loop-back image.
Specifically, the image receiving module 512 receives a sample loop image processed by the digital video image processing apparatus through the image receiving interface 516, and sends the received sample loop image to the image comparison and detection module 506, the image comparison and detection module 506 compares the sample loop image with the sample loop image according to the sample image, calculates a difference value between the sample image and the sample loop image, and generates a corresponding detection result according to the calculation result.
Wherein the sample loopback image comprises a video frame loopback image, an offset loopback image, and a distorted loopback image.
A result output module 508, a first input end of the result output module 508 is electrically connected to the output end of the image comparison detection module 506, an output end of the result output module 508 is electrically connected to the result sending interface 518, and the result output module 508 is configured to send the detection result according to the image detection result and the display mode.
The output end of the result display control module 510 is electrically connected to the second input end of the result output module 508, and the result display control module 510 is configured to output a selection instruction of a preset display mode.
Specifically, the result display control module 510 sends the received result display instruction to the result display module 508 through the I/O interface to change the display mode of the result display module 508.
The detection mode selection module 502, the sample image generation module 504, the image comparison detection module 506, the result output module 508, the result display control module 510, and the image receiving module 512 may be a field programmable gate array FPGA, a central processing unit CPU, a micro control unit MCU, or electronic devices with the same data processing function.
The embodiment of the present invention is described in detail above with reference to the accompanying drawings, and the present invention provides a digital video image distortion detection method, including: judging whether the video image detection mode is a video frame detection mode or not according to the received detection instruction; when the video image detection mode is judged to be the video frame detection mode, generating a video frame detection image; calculating a frame difference value between any frame loopback image in the video frame loopback image and a sample image of a corresponding frame in the video frame detection image according to the received video frame loopback image and the video frame detection image; and generating a video frame detection result according to the frame difference value. By the embodiment of the invention, the reliability of detecting the difference between the sample image and the sample loop-back image is improved, the complexity of judging the abnormality of the image processing device according to the image detection result is reduced, and the quality detection efficiency of the image processing device is improved.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. All changes, equivalents, modifications and the like which come within the spirit and principle of the invention are desired to be protected.
Claims (6)
1. A method for detecting distortion in a digital video image, comprising:
step 10, judging whether a video image detection mode is a video frame detection mode or not according to a received detection instruction;
step 20, when it is determined that the video image detection mode is the video frame detection mode, generating the video frame detection image, wherein the method specifically includes:
step 21, obtaining the resolution and image frame information of the video frame detection image;
step 22, calculating color values of pixel points in the video frame detection image according to the resolution and the image frame information, wherein the color values of the corresponding pixel points are calculated according to an abscissa x, an ordinate y, a current frame number z and a preset remainder function, wherein the preset remainder function is as follows:
wherein, x belongs to [0, 1919] on the abscissa, y belongs to [0, 1079] on the ordinate, and z belongs to [0, 255] on the frame number;
step 23, generating a video frame detection image according to the color value and a preset scanning frequency,
wherein the image frame information comprises a frame number;
step 30, calculating a frame difference value between any frame loopback graphic in the video frame loopback image and a sample image of a corresponding frame in the video frame detection image according to the received video frame loopback image and the video frame detection image;
and step 40, generating a video frame detection result in unit detection time according to the frame difference value.
2. The method for detecting distortion in a digital video image according to claim 1, wherein the step 30 further comprises:
step 31, selecting at least one pixel point in the sample image and recording the pixel point as a video frame sample point;
step 32, obtaining loop-back image pixel points of each frame in the video frame loop-back image, which correspond to the video frame sample points, and recording the loop-back image pixel points as video frame detection points;
step 33, calculating a pixel difference value of the video frame detection point in two adjacent frames;
and step 34, generating the video frame detection result according to the pixel difference value.
3. The digital video image distortion detection method of claim 1, wherein said step 10 further comprises:
step 11, when the video image detection mode is judged not to be the video frame detection mode, judging whether the video image detection mode is an offset detection mode;
step 12, when the video image detection mode is judged to be the offset detection mode, generating an offset detection image, wherein the offset detection image is an image with four corners, namely, white blocks with the width of 3 pixels respectively, a white block with the width of 6 at the center position and black at the rest positions;
step 13, calculating the position offset of any pixel point in the offset loopback image according to the received offset loopback image and the offset detection image;
and 14, generating an offset detection result according to the position offset.
4. The digital video image distortion detection method of claim 3, wherein said step 11 further comprises:
step 15, when it is determined that the video image detection mode is not the shift detection mode, generating a distortion detection image, wherein the method for generating a distortion detection image includes:
calculating the RGB color value of the corresponding pixel point according to a preset pixel block formula, and generating a distortion detection image, wherein the preset pixel block formula is as follows:
wherein, & is bitwise AND operation, and (x, y) is pixel point coordinates;
step 16, determining a pixel distortion point in the distortion loopback image according to the received distortion loopback image and the distortion detection image;
step 17, calculating a pixel distortion value corresponding to the pixel distortion point;
and step 18, generating a distortion detection result according to the pixel distortion point and the pixel distortion value.
5. The digital video image distortion detection method of claim 4, further comprising:
step 50, determining a first display mode according to the detection instruction;
step 60, according to the first display mode, sending the detection result,
wherein the detection result comprises the video frame detection result, the offset detection result, and the distortion detection result.
6. The digital video image distortion detection method of claim 5, further comprising:
step 70, determining a second display mode according to the received result display instruction;
and step 80, sending the detection result according to the second display mode.
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Citations (4)
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| US6141042A (en) * | 1997-06-23 | 2000-10-31 | Hewlett-Packard Company | Method and apparatus for measuring quality of a video transmission |
| CN102611894A (en) * | 2012-03-02 | 2012-07-25 | 华为技术有限公司 | Method, device and system for detecting video transmission packet loss |
| CN103945214A (en) * | 2013-01-23 | 2014-07-23 | 中兴通讯股份有限公司 | Terminal side time-domain video quality evaluation method and apparatus |
| CN107493471A (en) * | 2017-09-21 | 2017-12-19 | 北京奇艺世纪科技有限公司 | The computational methods and device of a kind of video transmission quality |
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| US6141042A (en) * | 1997-06-23 | 2000-10-31 | Hewlett-Packard Company | Method and apparatus for measuring quality of a video transmission |
| CN102611894A (en) * | 2012-03-02 | 2012-07-25 | 华为技术有限公司 | Method, device and system for detecting video transmission packet loss |
| CN103945214A (en) * | 2013-01-23 | 2014-07-23 | 中兴通讯股份有限公司 | Terminal side time-domain video quality evaluation method and apparatus |
| CN107493471A (en) * | 2017-09-21 | 2017-12-19 | 北京奇艺世纪科技有限公司 | The computational methods and device of a kind of video transmission quality |
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